• LIX Colloquium 2015 conferences, SEE Conference hosted by Ecole Polytechnique.


    The technical program of GSI2015 covers all the main topics and highlights in the domain of “Geometric Science of Information” including Information Geometry Manifolds of structured data/information and their advanced applications. This proceedings consists solely of original research papers that have been carefully peer-reviewed by two or three experts before, and revised before acceptance.
    The GSI15 program includes the renown invited speaker Professor Charles-Michel Marle (UPMC, Université Pierre et Marie Curie, Paris, France) that gives a talk on “Actions of Lie groups and Lie algebras on symplectic and Poisson manifolds”, and three (3) keynote distinguished speakers:
    Professor Marc Arnaudon (Bordeaux University, France): “Stocastic Euler-Poincaré reduction,”
    Professor Tudor Ratiu (EPFL, Switzerland): “Symetry methods in geometric mechanics,”
    Professor Matilde Marcolli (Caltech, US): “From Geometry and Physics to Computational Linguistics”,
    and a short course given by Professor Dominique Spehner (Grenoble University, France) on the “Geometry on the set of quantum states and quantum correlations” chaired by Roger Balian (CEA, France).
    The collection of papers have been arranged into the following seventeen (17) thematic sessions that illustrates the richness and versatility of the field:

    Dimension reduction on Riemannian manifolds, Optimal Transport, Optimal Transport and applications in Imagery/Statistics, Shape Space & Diffeomorphic mappings, Random Geometry & Homology, Hessian Information Geometry, Topological forms and Information, Information Geometry Optimization, Information Geometry in Image Analysis, Divergence Geometry, Optimization on Manifold, Lie Groups and Geometric Mechanics/Thermodynamics, Computational Information Geometry, Lie Groups: Novel Statistical and Computational Frontiers, Geometry of Time Series and Linear Dynamical systems, Bayesian and Information Geometry for Inverse Problems, Probability Density Estimation.

    Historical background
    As for the first edition of GSI (2013) and in past publications, GSI2015 addresses inter-relations between different mathematical domains like shape spaces (geometric statistics on manifolds and Lie groups, deformations in shape space, ...), probability/optimization & algorithms on manifolds (structured matrix manifold, structured data/Information, ...), relational and discrete metric spaces (graph metrics, distance geometry, relational analysis,...), computational and Hessian information geometry, algebraic/infinite dimensional/Banach information manifolds, divergence geometry, tensor-valued morphology, optimal transport theory, manifold & topology learning, ... and applications like geometries of audio-processing, inverse problems and signal processing.
    At the turn of the century, new and fruitful interactions were discovered between several branches of science: Information Science (information theory, digital communications, statistical signal processing,), Mathematics (group theory, geometry and topology, probability, statistics,...) and Physics (geometric mechanics, thermodynamics, statistical physics, quantum mechanics, ...).

    From Probability to Geometry
    Probability is again the subject of a new foundation to apprehend new structures and generalize the theory to more abstract spaces (metric spaces, shape space, homogeneous manifolds, graphs ....). A first attempt to probability generalization in metric spaces was developed by Maurice Fréchet in the middle of last century, in the framework of abstract spaces topologically affine and “distance space” (“espace distancié”). More recently, Misha Gromov, at IHES (Institute of Advanced Scientific Studies), indicates possibilities for (non-)homological linearization of basic notions of the probability theory and also the replacement of the real numbers as values of probabilities by objects of suitable combinatorial categories. In parallel, Daniel Bennequin, from Institut mathématique de Jussieu, observes that entropy is a universal co-homological class in a theory associated to a family of observable quantities and a family of probability distributions.

    From Groups Theory to Geometry
    As observed by Gaston Bachelard, “the group provides evidence of a mathematic closed on itself. Its discovery closes the era of conventions, more or less independent, more or less coherent”. About Elie Cartan’s work on Group Theory, Henri Poincaré said that “the problems addressed by Elie Cartan are among the most important, most abstract and most general dealing with Mathematics; group theory is, so to speak, the whole Mathematics, stripped of its material and reduced to pure form. This extreme level of abstraction has probably made my presentation a little dry; to assess each of the results, I would have had virtually render him the material which he had been stripped; but this refund can be made in a thousand different ways; and this is the only form that can be found as well as a host of various Garments, which is the common link between mathematical theories that are often surprised to find so near”.

    From Mechanics to Geometry
    The last elaboration of geometric structure on information is emerging at the inter-relations between “Geometric Mechanics” and ”Information Theory” that will be largely debated at GSI15 conference with invited speakers as C. M. Marle, T. Ratiu and M. Arnaudon. Elie Cartan, the master of Geometry during the last century, said ”distinguished service that has rendered and will make even the absolute differential calculus of Ricci and Levi-Civita should not prevent us to avoid too exclusively formal calculations, where debauchery indices often mask a very simple geometric fact. It is this reality that I have sought to put in evidence everywhere.”.
    For the anecdote, Elie Cartan, was the son of Joseph Cartan who was the village blacksmith, and Elie recalled that his childhood had passed under ”blows of the anvil, which started every morning from dawn”. One can imagine that the hammer blows given by Joseph on the anvil, giving shape and CURVATURE to the metal, insidiously influencing Elie’s mind with germinal intuition of fundamental geometric concepts. Alliance of Geometry and Mechanics is beautifully illustrated by this image of Forge, in this painting of Velasquez about Vulcan God (see Figure 1). This concordance of meaning is also confirmed by etymology of word “Forge”, that comes from late XIV century, “a smithy,” from Old French forge “forge, smithy” (XII century), earlier faverge, from Latin fabrica “workshop, smith’s shop”, from faber (genitive fabri) “workman in hard materials, smith”.
    As Henri Bergson said in book “The Creative Evolution” in 1907: “As regards human intelligence, there is not enough noticed that mechanical invention was first its essential approach ... we should say perhaps not Homo sapiens, but Homo faber. In short, intelligence, considered in what seems to be its original feature, is the faculty of manufacturing artificial objects, especially tools to make tools, and of indefinitely varying the manufacture.”

    Geometric Science of Information: a new Grammar of Sciences
    Henri Poincaré said that “Mathematics is the art of giving the same name to different things” (“La mathématique est l’art de donner le même nom `a des choses différentes.” in “Science et méthode”, 1908). By paraphrasing Henri Poincaré, we could claim that “Geometric Science of Information” is the art of giving the same name to different sciences. The rules and the Structures developed in GSI15 conference is a kind of new Grammar for Sciences.
    schema geometric science info.jpg

  • Topological and Geometrical Structure of Information - CIRM conference - August 27th- September 1st 2017


    Bandeau TGSI2017.png
    The conferences emphasize on an active participation of young researchers to discuss emerging topics of collaborative research. They are organised in half day and day sessions covering one central topic. Introductory courses open to students are proposed at the beginning of the sessions, then completed by more specialized one-hour presentation, and a session of working-discussion that tackle open questions and future development lines.

    Session 1: Information-theoretic geometry of metric measure spaces (particular and general).
    Organisers: Michel Ledoux (Institut de Mathématiques de Toulouse, France), Mokshay Madiman (University of Delaware, USA)
    Mini-course: Mokshay Madiman (University of Delaware, USA)
    Speakers: Thomas Courtade (University of California, Berkeley, USA), Nathael Gozlan (Université Paris-Est, France), Oliver Johnson (University of Bristol, UK), Jan Maas (IST, Austria), Karl-Theodor Sturm (Institut für Angewandte Mathematik, Germany).
    Abstract: This session will explore the geometry of particular instances as well as general classes of metric measure spaces as captured using the notion of entropy.

    Session 2: Information and topology
    Organisers: Pierre Baudot (INSERM, Fance), Daniel Bennequin (Université Paris Diderot, France), Michel Boyom (Université du Languedoc-Montpellier II, France), Herbert Gangl (Durham University, UK), Matilde Marcolli (Caltech, USA), John Terilla (Queens College, USA).
    Speakers: Daniel Bennequin (Université Paris Diderot, France), José Ignacio Burgos Gil (ICMAT, Spain), Michel Boyom (Université du Languedoc-Montpellier II, France), Philippe Elbaz-Vincent (Institut Fourier, France), Tom Leinster (University of Edinburgh, UK), Matilde Marcolli (Caltech, USA), John Terilla (Queens College, USA)
    Abstract: Arising from polylogarithmic functional equation, tropical semirings and probability theory studies, this session will adress the progresses acheived in caracterising the topology associated to information and probability theory, notably expressing some features of motive and operad.

    Session 3: Classical/Stochastic Geometric Mechanics and Lie Group Thermodynamics /Statistical Physics
    Organisers: Frédéric Barbaresco (Thales, France), Joël Bensoam (IRCAM, France).
    Speakers: Frédéric Barbaresco (Thales, France), Joël Bensoam (IRCAM, France), François Gay-Balmaz (LMD-ENS, France), Frédéric Hélein (Université Paris-Diderot, France), Bernhard Maschke (Claude Bernard University, France).
    Abstract: This session will address methods of variational calculus combined with stochastic analysis, Multi-Symplectic Geometry and Lie Group theories to study foundations of Stochastic Geometric Mechanics and Lie Group Thermodynamics.

    Session 4: Geometry of quantum states and quantum correlations
    Organisers: Dominique Spehner (Institut Fourier, France)
    Speakers: Madalin Guta (University of Nottingham, UK), Dominique Spehner (Institut Fourier, France), Karol Zyczkowski (Jagiellonian University, Poland) (...TBA).
    Abstract: The aim of this session is to explore the different Riemannian geometries that can be used to describe and quantify quantum correlations in composite quantum systems, together with their operational interpretations in quantum information theory.

    Session 5: Quantum states of geometry and geometry of quantum states.
    Organisers: Carlo Rovelli (Centre de Physique Theorique de Luminy, France)
    Speakers: Livine Etera (ENS Lyon, France), Antonino Marcianò (Fudan University, China), Carlo Rovelli (Centre de Physique Theorique de Luminy, France).
    Abstract: The objective of the session is to make the point on the way geometry and quantum correlations are related in quantum gravity. The focus would be on the recent developments in the possibility of describing quantum states of the geometry with long distance correlations. Session 6: Geometric Statistics on Manifolds and Shape Spaces.
    Organisers: Stéphanie Allasonnière (Paris V University, France), Xavier Pennec (INRIA sophia, France)
    Mini-course: Xavier Pennec (INRIA sophia, France), Alain Trouvé (ENS Cachan, France)
    Speakers: Marc Arnaudon (IMB, France), Aasa Feragen (DIKU, Denmark), Stanley Durrleman (ARAMIS lab, France), Ian Dryden (University of Nottingham, UK), Alice Le Brigant (IMB, Université de Bordeaux, France)
    Abstract: This session presents recent progresses in geometric statistics. In many applications domains such as computational anatomy and phylogenetics, computer vision, structural biology, one models data as elements of a manifold which is quotiented by a proper and isometric Lie group action (a shape space). Session 7: Geometry of Information for Neural Networks, Machine Learning, and Artificial Intelligence.
    Organisers: Nihat Ay (MPI-MIS, Germany), František Matúš (Institute of Information Theory and Automation, Czech Republic)
    Speakers: Nihat Ay (MPI-MIS, Germany), Tobias Fritz (Perimeter Institute, Canada), Luigi Malago (RIST, Romania), František Matúš (Institute of Information Theory and Automation, Czech Republic), Guido Montúfar (MPI-MIS, Germany), Johannes Rauh (Leibniz Universität, Germany), Milan Studený (Institute of Information Theory and Automation, Czech Republic).
    Abstract: This session will review the role in network analysis within the fields of artificial intelligence and machine learning, of geometric objects defined in terms of information equalities as well as information inequalities.

    Preliminary program Schedule:
    SCHEDULE .png
    Sponsor TGSI2017.png

  • Information Geometry and its Applications IV - June 13-17, 2016, Liblice, Czech Republic -

  • Geo-Sci-Info


    The Basque Centre for Applied Mathematics (BCAM),together with Ikerbasque, the Basque Foundation for Science, invites applications for one Research Professor position in Computational Fluid Dynamics and one Research Professor position in Data Science. This Research Professor call offers permanent contract positions for experienced researchers.

    ONE Research Professor position in Computational Fluid Dynamics.

    Basis and Rules:
    Application form:

    ONE Research Professor position in Data Science.

    Basis and Rules:
    Application form:

    We encourage immediate applications as the selection process will be ongoing.
    Desired skills and experience

    Candidates should provide:

    Letter of interest, including your research interest.
    2 recommendation letters (additional references may be requested during the evaluation)
    Statement of past experience (2-3 pages). Please, highlight your main results.
    Only researchers with a strong record of research will be considered. Women candidates are especially welcome.

    To submit your application please click on the "Go to application page" button.
    About the employer

    BCAM is a world-class research center on Applied Mathematics with a focus on interdisciplinary research in the frontiers of mathematics, attraction and training of talented scientists, development of new numerical and simulation methods, interaction with industry, and promotion of scientific and technological advances worldwide.

    Located in the Basque Country, it benefits from a long industrial tradition, and it is linked with the French Atlantic corridor, a region of excellence in Applied Mathematics. This context contributes to the task of building an excellence research center. BCAM counts with around 60 researchers from over 20 different countries with experience in some of the most prestigious research centers on their area, organized in 5 research areas and an administrative support team composed by 7 people.

    BCAM is a young research center that is facing its consolidation phase. In this sense, the scientific strategy of the center is based on three Scientific Platforms that have been set up in order to establish an interdisciplinary system capable of facing the challenges of Mathematical Science in a broad manner by bringing together Mathematics, Engineering and Sciences:

    Core in Applied Mathematics: PDE, Numerical Analysis, Fourier Analysis, Algebraic Geometry, Probability and Statistics.

    Computational Mathematics: Modeling andcomputer simulations using numerical, stochastic and Monte Carlo methods.

    Applications of Mathematics to Industry, Social Sciences and Health Sciences.

    Regarding human resources management, BCAM core values rely on people as its main asset, so, the continuous evolution of the HR strategy is key for the success of BCAM in order to adapt to the needs of the people, so BCAM decided to launch the HR Excellence in Research process (as the implementation of the European Charter for Researchers and Code of Conduct for the Recruitment) to enhance the efficiency, effectiveness and impact of the actions that BCAM should undertake to provide an attractive and supportive environment to researchers. BCAM was awarded with the HR Excellence in Research in May 2016.

  • Working group and Diffusion - submit events - new paper - projects - jobs - seminar (...)

  • Big Data Mathematical and Statistical Tools for Life Science - May 14-21 2016- Amirkabir University of Teheran-IPM, Tehran, Iran





    Saturday 14 : Opening and Introductive tutorials

    10h00:11h00 Opening and officials Welcome words of:
    Workshop general chairman,
    AUT President,
    Mathematical Department Director,
    IPM Mathematical Director
    International relations of AUT (Amir Golroo) and CS (Marc Zolver)
    Welcome of Mina Aminghafari and Adel Mohammadpour 11h00:12h30 Introductory tutorial on Big Data (Ali Mohammad-Djafari)
    Hierarchical Models and Variational Bayesian Approximation for Learning and Inference for Big Data 12h30 :14h00 Lunch 14h00:17h00 Introductory tutorial on Big Data (?)

    Sunday 15 : Mathematical and Statistical tools 1

    09h00:10h30 François Orieux : Fast MCMC algorithm for large scales inverses problems
    * 10h30:11h00 Tea and coffee break 11h00:12h30 Jean-François Giovannelli : Segmentation of piecewise constant images from incomplete, distorted and noisy data 12h30 :14h00 Lunch 14h00:17h00 Frédéric Pascal:

    Monday 16 : Mathematical and Statistical tools 2

    09h00:10h30 Stéphane Robin: Exact Bayesian inference for some models with discrete parameters 10h30:11h00 Tea and coffee break 11h00:12h30 Abdolreza Sayyareh: Non-nested and misspecified model selection for big data
    12h30 :14h00 Lunch 14h00:17h00 Pierre Baudot :Topological structures of information: theory, perspectives and applications to biological data and biological models.

    Tuseday 17 : Applications in Life Science

    09h00:10h30 Medical and Biomedical imaging systems
    Vincent Vigneron : Alzheimer's disease early detection with Deep-learning. The machine learning support
    10h30:11h00 Tea and coffee break 11h00:12h30 Environnemental applications
    Dominique Laffly: 12h30 :14h00 Lunch 14h00:17h00 Gholamreza Nakhaeizadeh: Applications of Big Data Mining in the Healthcare Industry

    Wednesday 18 : Applications in Life Science

    09h00:10h30 Medical and Biomedical imaging systems
    S. Morteza Najibi: Protein Classification and Prediction Using Multiple Ramachandran Distributions
    Abolfazl Fatholahzadeh:Building Incremental Homgraphs of Big Data
    10h30:11h00 Tea and coffee break 11h00:12h30 Medical and Biological imaging systems 12h30 :14h00 Lunch 14h00:17h00 Medical and Biological imaging systems

    Thursday 19 : Scientific and Touristic visit of Isfahan

  • Call for paper Entropy - new books - new papers - preprints


    SPRINGER launches the Journal "Information Geometry"

    springer information geometry.png

    The journal Information Geometry has taken up the challenge of how to think about and to look at mathematical science.
    In principle, Information Geometry can connect various branches of mathematical sciences to allow for uncertainty from geometric thinking. There is still great potential for exploring new paradigms to break through conventional notions. The journal will publish papers on such research along with those on application of information geometry, broadly construed, emphasizing both theoretical and computational aspects.
    Topics of interests will include, but not be limited to, the Fisher–Rao metric, dual connections, divergence functions, entropy/cross-entropy, Hessian geometry, exponential/mixture geodesics and projections, Q-statistics, quantum statistical inference and computation, computational information geometry, algebraic statistics, optimal transportation problems, deep neural networks, and related topics.
    The authors and audience of the journal will be interdisciplinary, coming from mathematics, statistics, machine learning, statistical and quantum physics, information theory, control theory, neural computation, complex networks, cognitive science, and allied disciplines.

  • Geo-Sci-Info

    green geometry.jpg


    © 2016 Ricardo Vega Bravo & Alberto Puime Otín

  • Geo-Sci-Info

    The CS-DC put at disposition of the members of the group a videoconference (bbb) system that can be used for:

    meeting for organisation, projects, review panels ... to record and diffuse on-line (streaming) conferences. The acquired video can then be put online and archived in the forum (contact for more information).

    Login: your full name
    Password: send an email to for reservation at least 24h before the conference you will be given the password that you can transmit to other participants.

    Material: it only requires a standard webcam-micro (usual laptop equipment) and to log on the website (a headphone with microphone integrated is recommended).
    Once logged on the website, the e-meeting interface loads and you will be asked to select your microphone, and then you can start your webcam (third button at the top left). You can also upload a pdf file that you manipulate just as in real conference, and that will be seen by all connected participants. The other participants can also share there webcam and microphone.

    visionconf principle.jpg

    If you need Professional video acquisition and post production for your conference, we recommend you the society COM-1film:
    +33 1 1 83 64 58 88
    They were in charge of GSI2015 video, if you want to see their work have a look at the video on

  • 12-17 sept 2016 Quiberon France - 5th summer school of theoretical Mecanic


    bandeau MGM.JPG

    Télécharger l'affiche


    La cinquième école d’été de mécanique théorique portera sur les méthodes géométriques en mécanique : introduction à la géométrie différentielle et à la géométrie Riemannienne, mécaniques Lagrangienne et Hamiltonienne, symétries et théorème de Noether, intégrateurs variationnels, point de vue géométrique sur la
    mécanique des milieux continus et sur la thermodynamique.

    École Thématique du CNRS, gratuite pour les personnels CNRS au titre de la formation permanente (nombre limité deplaces gratuites). Une subvention de l’AUM permet d’offrir également un tarif réduit à tous les académiques hors CNRS.

    Intervenants :

    Boris Kolev
    CMI, Marseille, France. Tudor Ratiu
    EPFL, Lausanne, Suisse. Gery de Saxcé
    Université des Sciences et Technologies de Lille 1, Laboratoire de Mécanique de Lille, Lille, France

    Comité d'organisation

    Patrick Ballard, Paris Aziz Hamdouni, La Rochelle Jean Lerbet, Évry Jean-Jacques Marigo, Palaiseau

    Comité Scientifique

    Patrick Ballard, Paris Anne-Sophie Bonnet-Ben Dhia, Palaiseau Michel Bornert, Marne-la-Vallée Alain Cimetière, Poitiers Gilles Francfort, Villetanneuse Aziz Hamdouni, La Rochelle Djimédo Kondo, Paris Jean Lerbet, Évry Jean-Jacques Marigo, Palaiseau Sébastien Neukirch, Paris Géry de Saxcé, Lille

    sponsor Bgm.JPG

  • 26-29 July 2016 at DIMACS, Rutgers University, NJ, USA


    Dimacs bandeau.JPG

    DIMACS Workshop on Distance Geometry: Theory and Applications
    26-29 July 2016 at DIMACS, Rutgers University, NJ, USA



    Farid Alizadeh (Rutgers Univ.) Leo Liberti (CNRS and Ecole Polytechnique, France)

    Scientific advisory committee:

    Amir Ali Ahmadi (Princeton) Marcia Fampa (Univ. Fed. Rio de Janeiro) Bill Jackson (Queen Mary, Univ. London) Nathan Krislock (Northern Illinois Univ.) Monique Laurent (CWI, The Netherlands) Therese Malliavin (CNRS Institut Pasteur) Michel Petitjean (Univ. of Paris 7) Nicolas Rojas (Yale) Amit Singer (Princeton) Henry Wolkowicz (Univ. Waterloo) Yinyu Ye (Stanford)

    Organization: DIMACS (Tami Carpenter, Rebecca Wright)

    Distance Geometry (DG) is a field of geometry which focuses on defining and working with geometrical objects using distances between points rather than the points themselves. From classical results such as Heron's theorem, Euler's conjecture on the rigidity of polyhedra, Maxwell's forces diagrams, and the link to positive semidefinite matrices, DG has seen a veritable "engineering renaissance" in the XX century. DG is used in architecture (rigidity of structures), spatial conformation of molecules from inter-atomic distances, localization of mobile sensors in communication networks, control of unmanned underwater vehicles, control of robotic arms, solution of problems in spatial logic, and more. One of the foremost problems in DG is that of completing a partially specified matrix so that it is a Euclidean distance matrix, either in a given dimension, or in any (unspecified) dimension. Schoenberg's link means that DG is tightly linked to Semidefinite Programming (SDP), which is one of the most popular tools to solve DG problems, especially in the field of sensor networks. Because so many diverse application fields appeal to DG, its development has been somewhat fragmented, with very similar concepts being introduced within separate communities with different names. The aims of this conference are: (i) to attempt to reconcile some of this fragmentation by inviting researchers from many different disciplines to take part; (ii) to facilitate communications of technical knowledge between the different application field communities working on DG; (iii) to provide incentives for unifying the field of DG.

    The workshop will be based on a series of invited tutorials and lectures. So far, the following people have accepted to speak. They are listed in no particular order, and the list is subject to change. Bon Connelly (Cornell), Bill Jackson (QM, Univ. London), Henry Wolkowicz (Univ. Waterloo), Amit Singer (Princeton), Jon Lee (UMich), Steven Gortler (Harvard), Therese Malliavin (Institut Pasteur, Paris), Ileana Streinu (Smith College), Shin-Ichi Tanigawa (Kyoto Univ.), Abdo Alfakih (UWindsor, Canada), Carlile Lavor (Univ. Campinas), Jayme Swarczfiter (Univ. Fed. Rio de Janeiro), Amir Ali Ahmadi (Princeton), Man-Cho So (Chinese Univ. Hong Kong), Marcia Fampa (Univ. Fed. Rio de Janeiro), Tibor Jordan (Eotvos Lorand Univ.), Georgina Hall (Princeton), Frank Parmenter (MIT), Hamza Fawzi (MIT), Pablo Parrilo (MIT), Antonios Varvitsiotis (Nat. Univ. Singapore), Nathan Krislock (Northern Illinois Univ.), Onur Ozyesil (Princeton), Simon Billinge (Columbia), Douglas Goncalves (Univ. Fed. Santa Catalina, Brazil), Martin Vetterli (EPFL).

    We are organizing a poster session, for which we are calling for posters. Please write to Leo Liberti if you're interested in presenting a poster.

    A special issue of Discrete Applied Mathematics, dedicated to the topic of this workshop, will be guest edited by the co-chairs.

  • Geo-Sci-Info

    Bandeau IEE brazil.JPG

    Information Geometry for Signal Processing and Communications
    Session of the 9th IEEE Sensor Array and Multichannel Signal Processing
    10th-13th July 2016, Rio de Janeiro, Brazil



    Charles C. Cavalcante Sueli I. R. Costa

    Technical Program
    The SAM Workshop is an important IEEE Signal Processing Society event dedicated to sensor array and multichannel signal processing. The organizing committee invites the international community to contribute with state-of-the-art developments in the field. SAM 2016 will feature plenary talks by leading researchers in the field as well as poster and oral sessions with presentations by the participants.

    Welcome to Rio de Janeiro! - The workshop will be held at the Pontifical Catholic University of Rio de Janeiro, located in Gávea, in a superb area surrounded by beaches, mountains and the Tijuca National Forest, the world's largest urban forest. Rio de Janeiro is a world renowned city for its culture, beautiful landscapes, numerous tourist attractions and international cuisine. The workshop will take place during the first half of July about a month before the 2016 Summer Olympic Games when Rio will offer plenty of cultural activities and festivities, which will make SAM 2016 a memorable experience.

    Research Areas
    Authors are invited to submit contributions in the following areas:
    Adaptive beamforming
    Array processing for biomedical applications
    Array processing for communications
    Big data
    Blind source separation and channel identification
    Computational and optimization techniques
    Compressive sensing and sparsity-based signal processing
    Detection and estimation
    Direction-of-arrival estimation
    Distributed and adaptive signal processing
    Intelligent systems and knowledge-based signal processing
    Microphone and loudspeaker array applications
    MIMO radar
    Multi-antenna systems: multiuser MIMO, massive MIMO and space-time coding
    Multi-channel imaging and hyperspectral processing
    Multi-sensor processing for smart grid and energy
    Non-Gaussian, nonlinear, and non-stationary models
    Optimization techniques
    Performance evaluations with experimental data
    Radar and sonar array processing
    Sensor networks
    Source Localization, classification and tracking
    Synthetic aperture techniques
    Space-time adaptive processing
    Statistical modelling for sensor arrays
    Tensor signal processing
    Waveform diverse sensors and systems

    Submission of papers - Full-length papers with 4 pages of content and 1 extra page only for references should be electronically submitted.

    Submission of Signal Processing Letters papers - Authors of IEEE Signal Processing Letters (SPL) papers will be given the opportunity to present their work at SAM 2016, subject to space availability and approval by the Technical Program Chairs. SPL papers published between 1st June, 2015 and 31st May, 2016 are eligible for presentation at SAM 2016. Requests for presentation of SPL papers should be made by emailing the Technical Program Chairs by 31st May, 2016. Approved requests for presentation must have one author/presenter registered for SAM 2016.

  • 4-8 april 2016, Nantes, France, GdR GeoSto Annual Meeting


    affiche Geosto2016.jpg

    Nantes, du 4 avril au 8 avril ( campus de la faculté des Sciences de l'Université de Nantes)


    Comité d'organisation : Jean-Christophe Breton, David Coupier, Bernard Delyon, Frédéric Lavancier, Ronan Le Guével, Nathalie Krell, Nicolas Pétrélis, Anne Philippe, Paul Rochet

    En partenariat avec le GDR 3477, la conférence Géométrie Stochastique a vocation à réunir annuellement les chercheurs qui étudient d'un point de vue théorique ou appliqué des modèles spatiaux aléatoires. Pour cette 5ème édition, les thèmes étudiés seront la géométrie aléatoire, les processus ponctuels, la statistique spatiale, les champs spatiaux, les processus spatio-temporels.

    La conférence se tiendra du 6 au 8 avril et sera précédée d'une école les 4 et 5 avril. Cette école proposera deux
    mini-cours :

    Introduction to random fields and scale invariance par Hermine Biermé (Poitiers) Introduction to Spatial Point Pattern Analysis par Yongtao Guan (Miami).

    Les incriptions sont ouvertes jusqu'au 31 janvier 2016 pour l'école et jusqu'au 27 février pour la conférence, dans la limite d'environ 70 participants.

    Comité d'organisation:

    Jean-Christophe Breton (Rennes 1) David Coupier (Lille 1) Bernard Delyon (Rennes 1) Nathalie Krell (Rennes 1) Frédéric Lavancier (Nantes) Ronan Le Guével (Rennes 2) Nicolas Pétrélis (Nantes) Anne Philippe (Nantes) Paul Rochet (Nantes)

    Orateurs confirmés

    Mathieu Carriere (Inria Saclay, Ile de France) Aurélie Chapron (Université de Rouen) Jean-François Coeurjolly (Université Pierre Mendès France, Grenoble 2) Yann Demichel (Université Nanterre Paris Ouest) Anne Estrade (Université Paris Descartes, Paris 5) Edith Gabriel (Université d'Avignon et des pays de Vaucluse) Yongtao Guan (University of Miami, États-Unis) Jonas Kahn (CNRS et Université de Toulouse) Simon Le Stum (Université Lille 1) José Rafael León (Universidad Central de Venezuela) Bertrand Michel (Université Pierre et Marie Curie, Paris 6) Jesper Møller (Aalborg University, Danemark) Werner Nagel (Jena Universität, Allemagne) Giovanni Peccati (University of Luxembourg) Nicolas Privault (Nanyang Technological University, Singapour) Arnaud Rousselle (Université de Bourgogne) Kaspar Stucki (Chalmers University, Suède) Donatas Surgailis (Vilnius University, Lituanie) Joseph Yukich (Lehigh University, États-Unis)

    Ecole (lundi 4 et mardi 5 avril)

    Accueil lundi 4 avril à 10h00
    Premier cours à 10h30

    Conférence (programme indicatif)

    Mercredi 6 avril

    9h30-10h Accueil et café
    10h00-10h40 J. R. Leon
    10h40-11h20 D. Surgailis
    11h20-12h00 A. Estrade
    12h00-14h00 déjeuner
    14h00-14h40 B. Michel
    14h40-15h20 M. Carriere
    15h20-16h00 pause café
    16h00-16h40 J. Kahn
    16h40-17h20 S. Le Stum
    17h20- ... Gdr meeting

    Jeudi 7 avril

    9h00-9h40 J. Moller
    9h40-10h20 Y. Guan
    10h20-11h00 pause café
    11h00-11h40 J.-F. Coeurjolly
    11h40-12h20 E. Gabriel
    12h20-14h20 déjeuner
    14h20-15h00 G. Peccati
    15h00-15h40 N. Privault
    15h40-16h20 café
    16h20-17h00 K. Stucki
    17h00-17h40 A. Rousselle

    Vendredi 8 avril

    9h00-9h40 W. Nagel
    9h40-10h20 J. Yukich
    10h20-11h00 pause café
    11h00-11h40 Y. Demichel
    11h40-12h20 A.Chapron
    12h20-14h20 déjeuner

  • Geo-Sci-Info

    bandeau gder day.JPG

    Outils en géométrie de l'information et probabilités dans les espaces abstraits pour le traitement du signal et des images
    Date : 4 décembre 2015

    Introduction :
    Le domaine de la géométrie de l'information et des probabilités dans les espaces abstraits (variétés différentielles, espaces métriques, graphes), qui s'appuient sur des résultats de mathématiciens, physiciens et de statisticiens de renoms tels que, sans être exhaustif, Fréchet, Koszul, Souriau, Balian, Fisher, Rao, Chentsov, Amari, offre aujourd'hui un cadre mature propice à générer de nouvelles avancées pour la communauté des traiteurs du signal et de l'image au sens large. En effet, abordant les problèmes de détection, d'estimation ou de classification sous l'angle de la géométrie différentielle et de la géométrie dans les espaces métriques, la géométrie de l'information et les probabilités dans les espaces abstraits permettent d'envisager des solutions à la fois élégantes et numériquement efficaces à de nombreux problèmes génériques en traitement du signal et de l'image, classiquement traités par l'algèbre linéaire. Enfin, ces approches géométriques ont notamment l'intérêt d'exploiter des métriques invariantes et ainsi d'écarter tout arbitraire dans le choix des formes considérées ou du système de coordonnées.

    Ainsi, en géométrie de l'information, une source (signal, image, vidéo, etc.) sera vue comme un point dans un espace métrique. Un tel espace est généralement une variété dotée d'une métrique riemannienne, ou pseudo-riemannienne grâce à laquelle il est possible de définir toute une série de grandeurs intrinsèques d'intérêt pour résoudre des problèmes visant à classer, analyser ou interpréter des signaux, images ou vidéo. En probabilité dans les espaces abstraits, il s'agit de façon similaire de redéfinir la notion de mesure et de densité sur ces variétés, ainsi que les outils statistiques associés.

    L'enjeu pour nous traiteurs du signal et de l'image est donc de savoir si l'utilisation de mesures, de critères, de lois a priori intrinsèques à ces espaces permet d'obtenir de nouveaux algorithmes, ou à défaut une meilleure connaissance de ceux qui existent déjà et une plus profonde connaissance des structures de l'information traitée.

    Les présentations :

    Présentation d'ouverture de la journée
    Frédéric Barbaresco THALES AIR SYSTEMS et yannick Berthoumieu Université de Bordeaux Groupe Signal et Image Laboratoire IMS Borne de Cramer-Rao intrinsèque sur les groupes de Lie
    Silvère Bonnabel : MINES ParisTech, PSL Research University, Centre for robotics. Lois Gaussiennes dans les espaces de matrices de covariance : nouveaux outils pour l'apprentissage statistique.
    Salem Said Université de Bordeaux Groupe Signal et Image Laboratoire IMS Quelques résultats récents en géométrie différentielle et ses applications en analyse de formes 3D et la reconnaissance d'activités humaines
    Mohamed Daoudi (Professeur), CRIStAL (UMR 9189), Telecom Lille Classification multi-utilisateurs simultanée de signaux électro-encéphalographiques par géométrie Riemannienne
    Louis Korczowski, Marco Congedo, and Christian Jutten Univ. Grenoble Alpes, GIPSA-lab Interpolation riemannienne pour l'estimation de la covariance d'un canal de communication
    Alexis Decurninge, Huawei Technologies Distance entre chemins dans une variété différentielle
    Alice Le Brigant, Université de Bordeaux et THALES AIR SYSTEMS Estimation non paramétrique de densité de probabilité sur les espaces de lois Gaussiennes munies de métriques Riemanniennes
    Emmanuel Chevallier, Ecole des Mines ParisTech, Fontainebleau Optimisation au deuxième ordre sur la variété des distributions gaussiennes
    Luigi Malago, Shinshu University Estimation adaptative pour les modèles de mélange dans les familles exponentielles
    Christophe Saint-Jean, Université de La Rochelle Détection de changements sur filtres de Kalman : utilisation de la distance entre modèles multivariés gaussiens au sens de la géométrie de l'information, estimée par tirs géodésiques ou calcul de bornes.
    Marion Pilté, Ecole des Mines ParisTech et THALES AIR SYSTEMS Consensus dans les espaces métriques CAT(k) avec topologie variable
    Bellachehab Anass, Telecom SudParis Espaces de courbes: métriques et densités
    S. Puechmorel et F. Nicol, ENAC, Toulouse

  • September 22-26 2014 University of Copenhagen - Machine Learning Lab


    machine learning lab.JPG

    Lectures overview

    Contents of Lectures by Shun-ichi Amari
    I. Introduction to Information Geometry - without knowledge on differential geometry

    Divergence function on a manifold Flat divergence and dual affine structures with Riemannian metric derived from it Two types of geodesics and orthogonality Pythagorean theorem and projection theorem Examples of dually flat manifold: Manifold of probability distributions (exponential families), positive measures and positive-definite matrices

    II. Geometrical Structure Derived from Invariance

    Invariance and information monotonicity in manifold of probability distributions f-divergence : unique invariant divergence Dual affine connections with Riemannian metric derived from divergence: Tangent space, parallel transports and duality Alpha-geometry induced from invariant geometry Geodesics, curvatures and dually flat manifold: Canonical divergence: KL- and alpha-divergence

    III. Applications of Information Geometry to Statistical Inference

    Higher-order asymptotic theory of statistical inference – estimation and hypothesis testing Neyman-Scott problem and semiparametric model em (EM) algorithm and hidden variables

    IV. Applications of Information Geometry to Machine Learning

    Belief propagation and CCCP algorithm in graphical model Support vector machine and Riemannian modification of kernels Bayesian information geometry and geometry of restricted Boltzmann machine: Towards deep learning Natural gradient learning and its dynamics: singular statistical model and manifold Clustering with divergence Sparse signal analysis Convex optimization
    Suggested reading:
    Amari, Shun-Ichi. Natural gradient works efficiently in learning. Neural Computation 10, 2 (1998): 251-276.
    Amari, Shun-ichi, and Hiroshi Nagaoka. Methods of information geometry. Vol. 191. American Mathematical Soc., 2007.

    Contents of Lectures by Nihat Ay
    I. Differential Equations:

    Vector and Covector Fields Fisher-Shahshahani Metric, Gradient Fields m- and e-Linearity of Differential Equations

    II. Applications to Evolution:

    Lotka-Volterra and Replicator Differential Equations "Fisher's Fundamental Theorem of Natural Selection" The Hypercycle Model of Eigen and Schuster

    III. Applications to Learning:

    Information Geometry of Conditional Models Amari's Natural Gradient Method Information-Geometric Design of Learning Systems

    Contents of Lectures by Nikolaus Hansen
    I. A short introduction to continuous optimization
    II. Continuous optimization using natural gradients
    III. The Covariance Matrix Adaptation Evolution Strategy (CMA-ES)
    IV. A short introduction into Python (practice session, see also here)
    V. A practical approach to continuous optimization using (practice session)
    Suggested reading:
    Hansen, Nikolaus. The CMA Evolution Strategy: A Tutorial, 2011
    Ollivier, Yann, Ludovic Arnold, Anne Auger, and Nikolaus Hansen. Information-Geometric Optimization Algorithms: A Unifying Picture via Invariance Principles. arXiv:1106.3708

    Contents of Lectures by Jan Peters
    Suggested reading:
    Peters, Jan, and Stefan Schaal. Natural actor critic. Neurocomputing 71, 7-9 (2008):1180-1190

    Contents of Luigi Malagò
    Stochastic Optimization in Discrete Domains
    I. Stochastic Relaxation of Discrete Optimization Problems
    II. Information Geometry of Hierarchical Models
    III. Stochastic Natural Gradient Descent
    IV. Graphical Models and Model Selection
    V. Examples of Natural Gradient-based Algorithms in Stochastic Optimization
    For the gradient flow movie click here.
    Suggested reading:
    Amari, Shun-Ichi. Information geometry on hierarchy of probability distributions IEEE Transactions on Information Theory 47, 5 (2001):1701-1711

    Contents of Lectures by Aasa Feragen and François Lauze
    I. Aasa's lectures

    Recap of Differential Calculus Differential manifolds Tangent space Vector fields Submanifolds of R^n Riemannian metrics Invariance of Fisher information metric If time: Metric geometry view of Riemannian manifolds, their curvature and consequences thereof

    II. François's lectures

    Riemannian metrics Gradient, gradient descent, duality Distances Connections and Christoffel symbols Parallelism Levi-Civita Connections Geodesics, exponential and log maps Fréchet Means and Gradient Descent

    Suggested reading:
    Sueli I. R. Costa, Sandra A. Santos, and Joao E. Strapasson. Fisher information distance: a geometrical reading. arXiv:1106.3708

    Contents of Tutorial by Stefan Sommer
    In the tutorial on numerics for Riemannian geometry on Tuesday morning, we will discuss computational representations and numerical solutions of some differential geometry problems. The goal is to be able to implement geodesic equations numerically for simple probability distributions, to visualize the computed geodesics, to compute Riemannian logarithms, and to find mean distributions. We will follow the presentation in the paper Fisher information distance: a geometrical reading from a computational viewpoint.
    The tutorial is based on an ipython notebook that is available here. Please click here for details.


    Principles of Information Geometry have been successfully applied in all major areas of machine learning, including supervised, unsupervised, and reinforcement learning, as well as in stochastic optimization. Information Geometry comes into play when we consider parametrized probabilistic models (e.g., in the context of stochastic behavioral policies, search distributions, stochastic neural networks, ...) and their adaptation. Technically speaking, in Information Geometry the space of probability distributions that can be represented by a parametrized probabilistic model is described as a manifold, on which the Fisher information metric defines a Riemannian structure. Through the geometry of the Riemannian manifold of distributions, optimization and statistics can be done directly on the space of distributions.
    Information geometry was founded and pioneered by Shun'ichi Amari in the 1980s, with statistical learning as one of the first applications. Due to the nonlinear nature of the space of distributions, the steepest ascent direction for adapting a probability distribution parametrized by a set of real-valued parameters (e.g., the mean and the covariance of a Gaussian distribution) is not the ordinary gradient in Euclidean space, but the so called natural gradient, defined with respect to the Riemannian structure of the space of distributions. The natural gradient is natural in the sense that it renders the adaptation invariant under reparametrization and changing representations, and it is closely linked to the Kullback-Leibler divergence often used for quantifying the similarity of distributions.
    The natural gradient for adapting probabilistic models has been successfully used in all major areas of machine learning, from supervised learning of neural networks over independent component analysis to reinforcement learning. In this PhD course there will, in particular, be lectures on supervised learning, reinforcement learning and stochastic optimization. Reinforcement learning refers to machine learning algorithms that improve their behavior based on interaction with the environment, whereas stochastic optimization refers to stochastic solutions to complex optimization problems for which we do not have an analytical description. Both in stochastic optimization and reinforcement learning, (intermediate) solutions are best described by probability distributions. In the one case, we consider distributions over potential actions to be taken in a certain situation. In the other case, we consider the search distribution describing which candidate solution to probe next. Thus, both the learning as well as the optimization process are best described by an iterative update of probability distributions.

    Confirmed Speakers

    Shun'ichi Amari, RIKEN Brain Science Institute Nihat Ay, Max Planck Institute for Mathematics in the Sciences and Universität Leipzig Nikolaus Hansen, Université Paris-Sud and Inria Saclay – Île-de-France Jan Peters, Technische Universität Darmstadt and Max-Planck Institute for Intelligent Systems Luigi Malagò, Shinshu University, Nagano Aasa Feragen, University of Copenhagen Francois Lauze, University of Copenhagen Stefan Sommer, University of Copenhagen

    Scientific content
    The course will consist of 5 days of lectures and exercises. In addition, students will be expected to read a pre-defined set of scientific articles on information geometry prior to the course, and write a report on information geometry and its potential use in their own research field after the course. The course will consist of three modules:

    A crash course on Riemannian geometry and numerical tools for applications of Riemannian geometry Introduction to Information Geometry and its role in Machine Learning and Stochastic Optimization Applications of Information Geometry

    Learning goals
    After participating in this course, the participant should

    Understand basic differential geometric concepts (manifolds, Riemannian metric, geodesics, manifold statistics) to the point where they can apply differential geometric concepts in their own research; Be able to implement basic numerical tools for differential geometric computations; Have a strong knowledge of information geometry and its role in machine learning and stochastic optimization; Be able to apply information theoretic approaches to machine learning and stochastic optimization in their own research;
    Have a basic knowledge of existing applications of information geometry.


    Christian Igel, University of Copenhagen Aasa Feragen, University of Copenhagen

    Københavns Universitet, Njalsgade 128, Bygning (building) 27, Lokal (room): 27.0.17

    The lectures are at the south campus of the University of Copenhagen, very close to the Metro station Islands Brygge. Room 27.0.17 in building 27 is on the ground floor. Click here for a map. See also Google maps.

  • Geo-Sci-Info

    Transition to Exascale Computing

    Target European proposal: FETHPC-02-2017

    Topic: Transition to Exascale Computing Subtopic: Mathematics and algorithms for extreme scale HPC systems and applications working with extreme data Types of action: RIA Research and Innovation action Planned opening : date Single-stage 12 April 2017 Deadline: 26 September 2017 17:00:00


    Topic description

    Specific Challenge:

    Take advantage of the full capabilities of exascale computing, in particular through high-productivity programming environments, system software and management, exascale I/O and storage in the presence of multiple tiers of data storage, supercomputing for extreme data and emerging HPC use modes, mathematics and algorithms for extreme scale HPC systems for existing or visionary applications, including data-intensive and extreme data applications in scientific areas such as physics, chemistry, biology, life sciences, materials, climate, geosciences, etc.

    Scope: Proposals should address one or more of the following subtopics:

    a) High productivity programming environments for exascale: Proposals should have as target to simplify application software development for large- and extreme-scale systems. This can include the development of more productive programming models and environments, the easier combination of different programming models, and using increased intelligence throughout the programming environment. Key aspects include managing data transfers, data locality and memory management, including support for heterogeneous and reconfigurable systems as well as dealing with inter-application dynamic load balancing and malleability, adapting to changes in the number of processors. Unified performance tools are required supporting HPC, embedded and extreme data workloads, on diverse target systems. APIs, runtime systems and the underlying libraries should support auto-tuning for performance and energy optimisation. Automated support for debugging and anomaly detection is also included under this subtopic. To provide simplified development and to ensure the maintainability of domain-specific languages (DSLs), DSL frameworks are required which target a general-purpose stable programming model and runtime. Since large future systems will require the use of multiple programming models or APIs, an important aspect is interoperability and standardisation of programming model, API and runtime as well as the composability of programming models (the capability of building new programming models out of existing programming model elements)

    b ) Exascale system software and management: Proposals should advance the state of the art in system software and management for node architectures that will be drastically more complex and their resource topology and heterogeneity will require OS and runtime enhancement, such as data aware scheduling. In the area of hardware abstraction, proposals should address run time handling of all types of resources (cores, bandwidth, logical and physical memory or storage) and controls, e.g. for optimised data coherency, consistency and data flow. For applications, proposals should address new multi-criteria resource allocation capabilities and interaction during task execution, with the aim to improve resilience, interactivity, power and efficiency. To cope with the exploding amount of data, the sequential analysis process (capture, store, analyse) is not sufficient; proposals should explore on-the-fly analysis methods offering reactivity, compute efficiency and availability. Graphical simulation interaction will require new real-time features; configuration and deployment tools will have to evolve to take into account the composability of software execution environments.

    c) Exascale I/O and storage in the presence of multiple tiers of data storage: proposals should address exascale I/O systems expected to have multiple tiers of data storage technologies, including non-volatile memory. Fine grain data access prioritisation of processes and applications sharing data in these tiers is one of the goals as well as prioritisation applied to file/object creates/deletes. Runtime layers should combine data replication with data layout transformations relevant for HPC, in order to meet the needs for improved performance and resiliency. It is also desirable for the I/O subsystem to adaptively provide optimal performance or reliability especially in the presence of millions of processes simultaneously doing I/O. It is critical that programming system interoperability and standardised APIs are achieved. On the fly data management supporting data processing, taking into account multi-tiered storage and involving real time in situ/in transit processing should be addressed.

    d) Supercomputing for Extreme Data and emerging HPC use modes: HPC architectures for real-time and in-situ data analytics are required to support the processing of large-scale and high velocity real-time data (e.g. sensor data, Internet of Things) together with large volumes of stored data (e.g. climate simulations, predictive models, etc.). The approaches should include support for real-time in-memory analysis of different data structures, direct processing of compressed data and appropriate benchmarking method for performance analysis. Interactive 3-D visualisation of large-scale data to allow users to explore large information spaces in 3-D and perform on-demand data analysis in real-time (e.g. large scale queries or analytics) should be addressed. Interactive supercomputing is required to execute complex workflows for urgent decision making in the field of critical clinical diagnostics, natural risks or spread of diseases; this implies adapting operational procedures of HPC infrastructures, developing efficient co-scheduling techniques or improving checkpoint/restart and extreme data management

    e) Mathematics and algorithms for extreme scale HPC systems and applications working with extreme data: Specific issues are quantification of uncertainties and noise, multi-scale, multi-physics and extreme data. Mathematical methods, numerical analysis, algorithms and software engineering for extreme parallelism should be addressed. Novel and disruptive algorithmic strategies should be explored to minimize data movement as well as the number of communication and synchronization instances in extreme computing. Parallel-in-time methods may be investigated to boost parallelism of simulation codes across a wide range of application domains. Taking into account data-related uncertainties is essential for the acceptance of numerical simulation in decision making; a unified European VVUQ (Verification Validation and Uncertainty Quantification) package for Exascale computing should be provided by improving methodologies and solving problems limiting usability for very large computations on many-core configurations; access to the VVUQ techniques for the HPC community should be facilitated by providing software that is ready for deployment on supercomputers.

    The Commission considers that proposals requesting a contribution from the EU between EUR 2 and 4 million would allow this specific challenge to be addressed appropriately. Nonetheless, this does not preclude submission and selection of proposals requesting other amounts. Proposals should clearly indicate the subtopic which is their main focus. At least one project per subtopic will be funded.

    Expected Impact:

    Contribution to the realisation of the ETP4HPC Strategic Research Agenda, thus strengthened European research and industrial leadership in HPC technologies.
    Successful transition to practical exascale computing for the addressed specific element of the HPC stack.
    Covering important segments of the broader and/or emerging HPC markets, especially extreme-computing, emerging use modes and extreme-data HPC systems.
    Impact on standards bodies and other relevant international research programmes and frameworks.
    European excellence in mathematics and algorithms for extreme parallelism and extreme data applications to boost research and innovation in scientific areas such as physics, chemistry, biology, life sciences, materials, climate, geosciences, etc.

  • "Directional statistics in Signal and Image Processing" Roscoff, Brittany, 22-26th August 2016.


    bandeau dissip2016.JPG


    The first edition of the summer school "Directional statistics in Signal and Image Processing" (DISSIP) will be held in Roscoff, Brittany, from the 22nd to the 26th of August 2016. The School is sponsored by the CNRS and the Persyval Labex. The summer school is open to everyone (PhD students, post-docs, researchers, etc) and is designed to provide a comprehensive state of the art on directional statistics and their usage in the field of signal and image processing, and at large in data science. The program of the summer school contains courses (both theoretical and applied) together with lab sessions and discussion times.

    sponsor dissip.JPG

    The summer school will take place at the CNRS Marine Station conference center, located in Roscoff, Brittany.

    Registration deadline: June 30th, 201
    Summer school: August 22nd-26th, 2016

    Scientific Committee

    Nicolas Le Bihan (Gipsa-Lab) Pr. Peter E. Jupp (School of Mathematics and Statistics, University of St Andrews) Pr. Jonathan H. Manton (Department of Electrical and Electronic Engineering, The University of Melbourne)

    Organizing Committee

    Nicolas Le Bihan (Gipsa-Lab) Events Office Gipsa-Lab (Gipsa-Lab)

    Events Office
    11 Rue des mathematiques
    Domaine Universitaire
    38402 Saint Martin d'Heres Cedex
    email: Send an email

    Registration must be made through the CNRS "Colloque Axur" Application: Registration

    Note that the registration is in two parts. You must first make a pre-registration. After that you will receive, by email, all the informations to complete your registration online. Note that registration must be completed (including payment) by the 30th of June 2016
    Note as well that no reimbursement will be possible once your registration is complete.
    Registration fees

    Academics/professionals: 475 euros PhD students: 220 euros CNRS fellows: free of charges Summer school lecturers: free of charges

    Payment should be made preferentialy by credit card.
    Alternate option for payement should be by order form

    Please contact the Events office at Gipsa-lab if you have any question.

    Follow the link to obtain the provisional program.

  • Geo-Sci-Info

    Dates: June 27 - July 15, 2016


    Location: Université Claude Bernard Lyon 1, Lyon-Villeurbanne, France ↓ Access details

    Objectives: The thematic period aims to provide an overview of the current state of research in calculus of variations, optimal transportation theory, and geometric measure theory, from both the perspectives of theory and applications. The scope of the conference ranges from rigorous mathematical analysis to modeling, numerical analysis, and scientific computing for real world applications in image processing, computer vision, physics, material science, computer graphics, biology, or data science.

    Three events in three weeks :

    Week1: June 27-July 1 → First Summer School Week2: July 4-8 → International conference "Calculus of Variations, Geometric Measure Theory, Optimal Transportation: from Theory to Applications" Week3: July 11-15 → Second Summer School


    First Summer School (June 27-July 1, 2016)
    Start: Monday, June 27th at 1pm
    End: Friday, July 1st at 2.30pm

    Three 7-hours lectures by

    Dorin Bucur (U. Savoie)
    Shape optimization of spectral functionals ↓Abstract
    In these lectures, isoperimetric type inequalities involving the spectrum of the Laplace operator (with some boundary conditions) will be seen from a shape optimisation point of view. Depending on the boundary conditions, the analysis of those problems (existence of solution, regularity, qualitative properties) is either related to a free boundary problem of Alt-Caffarelli type, or to a free discontinuity problem. I will make an introduction to this topic and present recent results, with a focus on Robin boundary conditions. In particular I will detail a monotonicity formula which is the key point for the (Ahlfors) regularity of the optimal sets.

    Guido De Philippis (CNRS & ENS Lyon)
    The selection principle: the use of regularity theory in proving quantitative inequalities ↓Abstract
    I will first introduce the topic of quantitative inequalities and give some examples. Then I will present a general technique to derive them based on the regularity theory for solutions of variational problems. The course will be mainly focused on the (quantitative) isoperimetric inequality and on the (quantitative) Faber-Krahn inequality

    Filippo Santambrogio (U. Paris-Sud)
    Optimal transport, optimal curves, optimal flows ↓Abstract
    The course will consist in an introduction to optimal transport theory with a special attention to the comparison between Eulerian and Lagrangian point of views, and between statical and dynamical approaches. Optimal flow versions of some issues of the problem will also be presented, and this will lead at the end of the course to the study of some traffic equilibrium problems.
    The course will consist of four lectures, roughly divided as follows:
    1 . Basic theory of Optimal Transport
    _ The problems by Monge and Kantorovich.
    _ Convex duality and Kantorovich potentials.
    _ Existence of optimal maps (Brenier Theorem) for strictly convex costs.
    2 . Wasserstein distances
    _ Definitions of the distances W_p induced by optimal transport costs.
    _ The duality between W_1 and Lipschitz functions and the topology induced by the distances W_p.
    _ The continuity equation and the curves in the space W_p.
    3 . Curves of measures and geodesics in the Wasserstein space
    _ From measures on curves to curves of measures and back.
    _ Constant-speed geodesics in the Wasserstein space.
    _ The Benamou-Brenier dynamical formulation of optimal transport.
    4 . Minimal flows
    _ An Eulerian formulation of the Monge problem with cost |x-y| (p=1): the Beckmann problem.
    _ From measures on curves to vector flows and back.
    _ Extensions to traffic congestion models.

    Second Summer School (July 11-15, 2016)
    Start: Monday, July 11th at 9am
    End: Friday, July 15th at 6pm

    Three 7-hours lectures by

    Daniel Cremers (Munich)
    Variational Methods for Computer Vision ↓Abstract
    Variational methods are among the most classical and established methods to solve a multitude of problems arising in computer vision and image processing. Over the last years, they have evolved substantially, giving rise to some of the most powerful methods for optic flow estimation, image segmentation and 3D reconstruction, both in terms of accuracy and in terms of computational speed. In this tutorial, I will introduce the basic concepts of variational methods. I will then focus on problems of geometric optimization including image segmentation and 3D reconstruction. I will show how the regularization terms can be adapted to incorporate statistically learned knowledge about our world. Subsequently, I will discuss techniques of convex relaxation and functional lifting which allow to computing globally optimal or near-optimal solutions to respective energy minimization problems. Experimental results demonstrate that these spatially continuous approaches provide numerous advantages over spatially discrete (graph cut) formulations, in particular they are easily parallelized (lower runtime) and they do not suffer from metrication errors (better accuracy).

    Jérôme Darbon (CNRS & ENS Cachan)
    On Optimization Algorithms in Imaging Sciences and Hamilton-Jacobi equations ↓Abstract
    The course will consist of two parts
    1. Total variation minimization and maximal flows in graphs
    Applications to image processing
    Anisotropic mean curvature flow
    2. Optimization in image processing, Hamilton-Jacobi equations, and optimal control -----------------------------------------------------------------------------------------------------------------------------_

    Quentin Mérigot (CNRS & U. Paris-Dauphine)
    Computational optimal transport ↓Abstract
    Optimal transport has been used as a powerful theoretical tool to study partial differential equations, differential geometry and probability for a few decades. In comparison, its use in numerical applications is much more recent, not because of lack of interest but rather because of computational difficulties. The simplest discretization of the optimal transport problem lead to combinatorial optimization problems for which can only be solved with superquadratic cost. On the other hand, the partial differential equations arising from optimal transport are fully non-linear Monge-Ampère equations, for which there did not exist robust and efficient numerical solvers until recently. This course will present a variety of approaches to solve optimal transport and related problems, with applications in mind, such as:

    Entropic penalization and Wasserstein barycenters Benamou-Brenier algorithm, gradient flows and simulation of non-linear diffusion equations Monge-Ampère equation, computational geometry and convexity constraints Semi-discrete optimal transport and inverse problems in geometric optics Measure-preserving maps, optimal quantization and Euler's equation for incompressible fluids
    -----------------------------------------------------------------------------------------------------------------------------_ International conference "Calculus of Variations, Geometric Measure Theory, Optimal Transportation: from Theory to Applications" (July 4-8, 2016)
    Start: Monday, July 4th at 1pm
    End: Friday, July 8th at 2pm
    Conference program will be available soon

    Confirmed speakers
    Giovanni Alberti (Università di Pisa, Italy)
    Jean-François Aujol (Université de Bordeaux, France)
    Giovanni Bellettini (Università di Roma "Tor Vergata", Italy)
    Virginie Bonnaillie-Noël (École Normale Supérieure de Paris, France)
    Guy Bouchitté (Université du Sud-Toulon-Var, France)
    Blaise Bourdin (Lousiana State University, USA)
    Lia Bronsard (McMaster University, Canada)
    Michael Bronstein (Università della Svizzera Italiana, Switzerland)
    Almut Burchard (University of Toronto, Canada)
    Daniel Cremers (Technische Universität München, Germany)
    Qiang Du (Columbia University in the City of New York, USA)
    Selim Esedoḡlu (University of Michigan, USA)
    Ilaria Fragalà (Politecnico di Milano, Italy)
    Adriana Garroni (Università di Roma "La Sapienza", Italy)
    Young-Heon Kim (University of British Columbia, Canada)
    Jacques-Olivier Lachaud (Université de Savoie, France)
    Francesco Maggi (University of Texas at Austin, USA)
    Maks Ovsjanikov (École Polytechnique, France)
    Manuel Ritoré (Universidad de Granada, Spain)
    Dejan Slepčev (Carnegie Mellon University, USA)
    Jeremy Tyson (University of Illinois at Urbana-Champaign, USA)
    Bozhidar Velichkov (Université Grenoble Alpes, France)
    Max Wardetsky (Georg-August-Universität Göttingen, Germany)
    Stefan Wenger (University of Fribourg, Switzerland)
    Benedikt Wirth (Universität Münster, Germany)

    Accommodation for PhD students and postdoctoral young researchers
    Hotel accommodation (in shared double occupancy rooms) is offered to a maximal number of 60 PhD students or postdoctoral young researchers. Rooms are attributed in registration order. Use the pre-registration form below for application.

    Registration fees
    60 euros per week for permanent researchers
    30 euros per week for PhD students and postdoctoral researchers
    No registration fees for local researchers and local students
    Included with conference registration fees:

    hotel accommodation for a limited number of 60 PhD students or postdoctoral young researchers (rooms are attributed in registration order) daily coffee and refreshment breaks social events conference dinner

    Registration (deadline for payment: Monday, June 6)
    NB: Week 1 being labeled as a CNRS Thematic School, it benefits from a specific funding which requires a separate registration/payment procedure. We sincerely apologize for the total inconvenience of the whole registration process.

    Step 1: If you have not done it already, fill this pre-registration form Step 2: For Week 1 (First Summer School, partially funded by CNRS), register and pay here→ Registration/Payment for Week #1 Step 3: [[ Important ]] Log out from Week 1 registration process using this link Step 4: For Weeks 2 and/or 3 (International Conference and/or Second Summer school), register and pay here→ Registration/Payment for Weeks #2 and/or #3 Step 5: [[ Important ]] Log out from Weeks 2-3 registration process using this link Step 6: Congratulations, you did it! (and many thanks for your patience...)

    Scientific Committee
    Lorenzo Brasco
    Dorin Bucur
    Antonin Chambolle
    Thierry De Pauw
    Guy David
    Vincent Feuvrier
    Antoine Lemenant
    Quentin Mérigot
    Benoit Merlet
    Vincent Millot
    Laurent Moonens
    Edouard Oudet
    Olivier Pantz
    Séverine Rigot
    Filippo Santambrogio

    Organizing Committee
    Elie Bretin
    Sarah Delcourte
    Simon Masnou
    Hervé Pajot

    For any questions about the thematic period, please contact us at this email address.

  • 16th June 2016 - University Paris 13


    Journée d’exposés en "Combinatoire, Opérades et Probabilités"


    Université Paris 13 (salle B405 du LAGA)
    Indications pour se rendre à Paris 13

    Programme :

    10h-11h : "Approche homotopique des probabilités libre d’après Drummond-Cole—Park—Terilla" [Bruno Vallette, Université Paris 13] 11h30-12h30 : "Des séries en arbres aux séries de type Dirichlet" [Frédéric Chapoton, Université de Strasbourg] Déjeuner 14h-15h : "Sur une généralisation des probabilités libres en matrices aléatoires" [Camille Male, Université Paris Descartes] 15h30-16h30 : "Cumulants libres non-commutatifs" [Jean-Yves Thibon, Université Paris-Est Marne-la-Vallée]

    Résumés :

    "Approche homotopique des probabilités non-commutatives d’après Drummond-Cole—Park—Terilla" [Bruno Vallette, Université Paris 13]
    Le but de cet exposé est d’offrir un résume aussi élémentaire que possible de l’approche homotopique proposée par Drummond-Cole—Park—Terilla des cumulants apparaissant en probabilité non-commutative. Le point principal consiste à interpréter ces derniers comme des infini-morphismes des algèbres à homotopie près sur certaines opérades de Koszul. On retrouve alors toutes les formules de cumulants des probabilités non-commutative à l’aide des formules d’inversion des infini-isomorphismes et de l’action du groupe de jauge de la théorie de la déformation des algèbres à homotopie près. Aucun prérequis n'est nécessaire pour suivre cet exposé; toutes les notions seront rappelées, ce qui permettra aussi de servir d’introduction aux autres exposés de la journée. "Des séries en arbres aux séries de type Dirichlet" [Frédéric Chapoton, Université de Strasbourg]
    Je présenterai deux séries en arbres particulières qui jouent un rôle comparable à celui de l'exponentielle et du logarithme, et qui apparaissent naturellement en analyse numérique. J'expliquerai ensuite comment une déformation du "logarithme en arbres" est motivée par certaines considérations algébriques. Je donnerai une description des coefficients de ce q-logarithme en arbres
    en termes de certains polytopes, et éventuellement la relation entre certains de ces coefficients et des séries de type Dirichlet. "Sur une généralisation des probabilités libres en matrices aléatoires” : [Camille Male, Université Paris Descartes]
    Certains modèles de matrices aléatoires hermitiennes ont la propriété de se diagonaliser dans une base qui n'est pas "asymptotiquement uniformément distribuée" lorsque la taille des matrices tend vers l'infini, contrairement aux matrices classiques de Wigner ou de Wishart. En conséquence, les distributions asymptotiques de valeurs propres de polynômes hermitiens en de telles matrices indépendantes diffèrent parfois des prédictions données par les probabilités libres.
    Un espace de probabilités non commutatif étant une algèbre munie d'une forme linéaire, nous verrons qu'il est possible grace aux opérades d'introduire une notion de variable non commutative plus riche qui permet de calculer les moments de ces distributions dans des cas variés. Les résultats sont exprimés en termes d'une notion d'indépendance qui unifie l'indépendances classique (tensorielle), l'indépendance libre de Voiculescu et encode également d'autres relations. "Cumulants libres non-commutatifs” [Jean-Yves Thibon, Université Paris-Est Marne-la-Vallée]
    L'équation fonctionnelle définissant les cumulants libres dans le cas d’une seule variable aléatoire peut être relevée successivement à l'algèbre de Faà di Bruno non-commutative, puis au groupe d'une opérade libre. La solution de cette équation prend en compte le cas d'une mesure à valeurs opératorielles, et redonne la formule de Speicher dans le cas d'une mesure scalaire. On peut aussi interpréter cette équation comme une généralisation de celle d'Ebrahimi-Fard et Patras.

    Tous les détails de cette rencontre sont disponibles à l’adresse suivante :

    Deux pauses cafés et le déjeuner sont prévus. Si vous pensez venir, merci de nous prévenir par courriel à vallette [ at]
    N’oubliez pas de venir avec une copie de ce message ou de la page de la rencontre pour pouvoir entrer dans le campus.

    Organisateurs :
    Eric Hoffbeck et Bruno Vallette
    Soutiens :
    Pole Mathstic Paris13 et projet ANR SAT

  • 3rd International Electronic and Flipped Conference on Entropy and Its Applications - 1-10 nov 2016


    Welcome from the Chair of the Forum


    You are cordially invited to participate in the 3rd International Electronic and Flipped Conference on Entropy and Its Applications. This event is designed to bring together researchers working in the field to present and discuss their recent contributions, without the need to travel.

    The field of entropy-related research has been particularly fruitful in the past few decades, and continues to produce important results in a vast range of fields spanning all branches of the sciences, engineering, social sciences, economics / finance and the humanities. We welcome your contributions on theoretical insights into the entropy concept and on information theory, and on practical applications of the maximum entropy method in any field.

    This year, we will also make every effort to facilitate interaction and the exchange of ideas during the conference period. All presenters will be asked to prepare an audio or video of their presentation. This will be uploaded onto the conference platform in advance, for viewing by others during the conference period - possibly one of the first “flipped mode” conferences in the world! We will also schedule an online discussion period for each presentation. We will announce further details of the technological requirements and schedule in due course.

    The conference will be organized into six sessions, which reflect the inter-disciplinary nature of entropy and its applications:

    Section A
    Physics and Engineering: Thermodynamics, Statistical Mechanics, the Second Law of Thermodynamics, Reversibility, Quantum Mechanics, Black Hole Physics, Maximum Entropy Methods, Maximum Entropy Production, Evolution of the Universe Section B
    Information Theory: Shannon Entropy, Kullback-Leibler Divergence, Channel Capacity, Alternative Entropies, and Applications Section C
    Complex Systems: Self-Organization, Chaos and Nonlinear Dynamics, Simplicity and Complexity, Networks, Symmetry Breaking, Similarity Section D
    Chemistry and Biology: Chemical Networks, Energy, Enthalpy, Maximum Entropy Methods, Biological Networks, Evolution, DNA and RNA, Diversity Section E
    Machine Learning and Systems Theory: Artificial Intelligence, Neural Networks, Cybernetics, Robotics, Man–Machine Interfaces, Causality Section P
    Posters: In this section, posters can be presented stand-alone, i.e., without an accompanying proceedings paper or conference presentation. Posters will be available online on this website during and after the e-conference. However, posters will not be added to the proceedings of the conference.

    Accepted papers will be published in the proceedings of the conference, and selected/extended papers will be considered for publication in Entropy with a 20% discount off the APC. Entropy is an open access publication journal of MDPI in the field of entropy and information theory.

    Important Dates:
    Abstract Submission: 18 September 2016
    Notification of Acceptance: 30 September 2016
    Submission of Full Paper and Poster/Presentation: 20 October 2016
    Conference Open: 1-10 November 2016

    Please do not hesitate to contact us if you have questions. It is my pleasure to welcome you to the Third e-Conference on Entropy!

    Best regards,
    Robert Niven
    The University of New South Wales, Canberra, Australia
    Google Scholar
    Contact me on ResearchGate!

    Robert Niven has a BSc (Hons) in chemistry and geology and a PhD in civil and environmental engineering, both from The University of New South Wales, Australia. He is a long-standing Editorial Board Member and reviewer for Entropy (since 2007), and was Chair of the MaxEnt 2013 conference in Canberra, Australia. Over the past decade, Dr Niven has developed new theoretical perspectives into the entropy concept based on combinatorial reasoning, and has also pioneered new applications of the maximum entropy method for the analysis of dissipative non-equilibrium systems, fluid flow systems, dynamical systems and flow networks. This research has been recognized by a number of international fellowships and awards, including Japan Society for the Promotion of Science Invitation Fellowship (2006), Marie Curie Incoming International Fellowship, Denmark (14 months, 2007‑08); Endeavour Executive Award (2010), Isaac Newton Institute Visiting Fellowship (2010), CNRS Fellowship, France (2011) and Invited Professor, Institut PPrime / Région Poitou-Charentes, France (11 months, 2014). His most recent research interests include the maximum entropy analysis of turbulent flow systems, graphical systems and urban flow networks, including distributed power generation, water distribution and vehicular systems

    Entropy Journal

  • Geo-Sci-Info

    Cher(e)s Collègues,

    Nous avons le plaisir d'annoncer le séminaire suivant:

    Vendredi 24 juin, 15h00, École polytechnique, salle de conférence du CPHT (rez de chaussée de l'aile 0 des laboratoires)

    Rajendra Bhatia (Indian Statistical Institute, New Delhi)

    Titre: Bures-Wasserstein distance between positive definite matrices

    Résumé: We will discuss from the perspective of matrix analysis an interesting metric on the space of positive definite matrices, that has connections to several areas like quantum information, statistics, optimal transport and Riemannian geometry.

    En raison des mesures de sécurité, un document d'identité pourra vous etre demandé pour accéder à l'École. Nous vous recommandons aussi d'avoir avec vous une copie de cette annonce.

    Bien cordialement
    Les organisateurs

    Stéphane Gaubert (INRIA et CMAP)
    Éric Goubault (LIX)

    PS. Pour venir à l'École polytechnique:

    L'aile 0 des laboratoires est indiquée par le numéro 0 sur le plan suivant:
    Nous recommandons d'accéder à l'aile 0 par l'entrée donnant sur le parking des laboratoires: cette entrée fait face à la salle de conférence.

  • National University of Singapore - 4 - 31 July 2016


    Schedule and Abstracts PDF

    Tutorial on Manifolds of Diffeomorphisms, EPDiff
    Martin Bauer, University of Vienna, Austria

    Riemannian geometries on the space of curves I Riemannian geometries on the space of curves II
    Abstract (1) and (2): The space of curves is of importance in the field of shape analysis. I will provide
    an overview of various Riemannian metrics that can be defined thereon, and what is known about the
    properties of these metrics. I will put particular emphasis on the induced geodesic distance, the
    geodesic equation and its well-posedness, geodesic and metric completeness and properties of the
    curvature. In addition I will present selected numerical examples illustrating the behaviour of these
    metrics. Right invariant metrics on the diffeomorphism group
    The interest in right invariant metrics on the diffeomorphism group is fuelled by its relations to
    hydrodynamics. Arnold noted in 1966 that Euler's equations, which govern the motion of ideal,
    incompressible fluids, can be interpreted as geodesic equations on the group of volume preserving
    diffeomorphisms with respect to a suitable Riemannian metric. Since then other PDEs arising in
    physics have been interpreted as geodesic equations on the diffeomorphism group or related spaces.
    Examples include Burgers' equation, the KdV and Camassa-Holm equations or the Hunter-Saxton
    Another important motivation for the study of the diffeomorphism group can be found in its
    appearance in the field of computational anatomy and image matching: the space of medical images
    is acted upon by the diffeomorphism group and differences between images are encoded by
    diffeomorphisms in the spirit of Grenander's pattern theory. The study of anatomical shapes can be
    thus reduced to the study of the diffeomorphism group.
    Using these observations as a starting point, I will consider the class of Sobolev type metrics on the
    diffeomorphism group of a general manifold M. I will discuss the local and global well-posedness of
    the corresponding geodesic equation, study the induced geodesic distance and present selected
    numerical examples of minimizing geodesics. The space of densities
    I will discuss various Riemannian metrics on the space of densities. Among them is the Fisher--Rao
    metric, which is of importance in the field of information geometry. Restricted to finite-dimensional
    submanifolds, so-called statistical manifolds, it is called Fisher's information metric. The Fisher--Rao
    metric has the property that it is invariant under the action of the diffeomorphism group. I will show,
    that on a closed manifold of dimension greater than one, every smooth weak Riemannian metric on
    the space of smooth positive probability densities, that is invariant under the action of the
    diffeomorphism group, is a multiple of the Fisher--Rao metric.

    Tutorial on Manifolds of Diffeomorphisms, EPDiff
    Martins Bruveris, Brunel University London, UK

    Lecture I - Mapping spaces as manifolds
    This lecture will give an introduction to differential geometry in infinite dimensions. The main objects of
    shape analysis - the diffeomorphism group, the spaces of curves, surfaces, densities - can all be
    modelled as infinite-dimensional manifolds.
    Lecture II - Riemannian geometry in infinite dimensions
    Parts of Riemannian geometry generalise easily from finite to infinite dimensions. These include the
    definition of metric, covariant derivative, geodesic equations and curvature. But there are also
    qualitative differences, in particular with the distinction between strong and weak Riemannian metrics.
    This lecture will show some of the purely behaviour that can be encountered in infinite dimensions.
    Lectures III and IV - Riemannian metrics induced by the diffeomorphism group
    The purpose of these lectures is to explore the geometry of Riemannian metrics on the space of
    curves and landmarks that are induced by the action of the diffeomorphism group. These metrics
    correspond to exact matching of curves and landmarks via LDDMM. We will look at the induced
    metrics, geodesic equations and the geodesic distance.

    Introduction to the Differential Geometry
    Joan Alexis Glaunès (Université Paris Descartes, France) and
    Sergey Kushnarev (Singapore University of Technology and Design)

    Definition of a manifold, Tangent Vectors and Tangents Spaces, Pushforwards, Vector Fields. Tangent bundle and a Cotangent Bundle, Pullbacks, Tensors, Differential Forms. Submersions, Immersions, Embeddings, Submanifolds (Embedded, Immersed) Integral Curves and Flows, Lie Derivatives. Riemannian Metrics. Connections. Riemannian Geodesics and Distance (exp map, normal coordinates, geodesics and minimizing
    distances). Curvature.

    Diffeomorphic Models and Matching Problems in the Discrete Case
    Joan Alexis Glaunès, Université Paris Descartes, France
    This talk will be an introduction and on overview of the framework of diffeomorphic mappings
    (LDDMM) for estimating deformations between shapes, and its formulation for discrete problems via
    reproducing kernels. I will present the classical construction of the group of diffeomorphisms, and
    explain how by considering different types of actions on this group, it can be used to estimate
    deformations between different types of geometric data: images, points, surfaces, etc. I will show
    some experiments and studies to illustrate.

    Geodesic Equations and Shooting Algorithms for Matching and Template Estimation
    Joan Alexis Glaunès, Université Paris Descartes, France
    In this talk I will explain the link between diffeomorphic mappings and shape spaces, i.e. Riemannian
    metrics on sets of shapes. I will explain how the metric on the group of diffeomorphisms induces a
    metric on the space of shapes, and detail the geodesic equations in the finite dimensional case
    (manifold of landmarks), which is the case in use in practice for many problems once data has been
    discretised. I will present different algorithms which are based on these equations (geodesic shooting
    algorithms): matching, template estimation, geodesic regression, and explain how all this can be
    actually implemented.

    Models for Diffeomorphic Mappings between Submanifolds: measures, currents, varifolds
    Joan Alexis Glaunès, Université Paris Descartes, France
    This talk will focus on some models for defining data attachment terms for matching problems
    between submanifolds (curves or surfaces) which are widely used for diffeomorphic mappings. These
    are all based on the same idea of defining dual RKHS spaces and using the corresponding norm as a
    data attachment term between shapes. This uses mathematical concepts such as currents or
    varifolds, which come from geometric measure theory and which I will introduce. I will present both
    continuous and discrete forms of these models, and show some outputs of algorithms

    Reproducing Kernels in the Vectorial Case
    Joan Alexis Glaunès, Université Paris Descartes, France
    The theory of reproducing kernels and Reproducing Kernel Hilbert Spaces (RKHS) is extensively
    used in the discrete formulation of the LDDMM setting, and in corresponding algorithms. It is also a
    fundamental concept in other areas, such as statistical learning. I will present some basic concepts of
    this theory in the general case of RKHS of vector fields, and explain how this theory can be used for
    interpolation problems, and how it is linked to the LDDMM setting. I will also present shortly a recent
    study about translation and rotation invariant kernels, which allows in particular to consider spaces of
    divergence free or irrotational vector fields for deformation analysis.

    Lie Groups and Lie Group Actions
    Richard Hartley, Australian National University, Australia
    I will talk about Lie groups and Lie group actions on manifolds, with particular consideration for
    applications in Computer Vision. Lie groups play a significant role in Computer Vision, particularly
    groups such as SO(3), the group of 3-D rotations, SE(3), the group of Euclidean motions, and
    PGL(2,R) and PGL(3, R), the groups of 2 and 3-dimensional projective transformations. In addition,
    Lie group actions on such manifolds as the Stiefel manifolds (yielding Grassman manifolds as a space
    of orbits) and the action of O(2) on SO(3) x SO(3), yielding the Essential manifold, as well as Shape
    manifolds as an orbit space of an action of similarity transforms, are common examples where Lie
    group actions give rise to Riemannian manifold structures. Applications are in the areas of Lie group
    tracking, averaging (for instance rotation averaging), and kernels on manifolds such as shape
    manifolds and Grassman manifolds, all with important applications in computer vision and robotic

    Tutorial on Wavelets
    Hui Ji, National University of Singapore
    This lecture focuses on the introduction to wavelet frame and its applications in imaging and vision.
    The goal to expose audience to important topics in wavelet frames with strong relevance to visual
    data processing, in particular image processing/analysis. The audience will also learn how to apply
    these methods to solve real problems in imaging and vision. The lecture is an inter-disciplinary one
    that emphasizes both rigorous treatment in mathematics and motivations from real-world applications.

  • CIRM Workshop: SIGNAL, IMAGE, GEOMETRY, MODELLING, APPROXIMATION + session Claude Shannon- October 31-November 4th, 2016 - Marseille, France


    Workshop SIGMA'2016


    Important: all the participants are hosted in the CIRM.

    SIGMA'2016 aims at gathering specialists of the following main domains: Signal-Image, Geometric Modelling, Computational Geometry, Approximation. The workshop will be composed of invited plenary talks given by experts in these fields and contributed presentations.

    SIGMA'2016 which will take place from Monday, October 31st, to Friday, November 4th, 2016, in the International Center for Mathematical Meetings (CIRM), located on the Campus of Luminy, Marseille, France. It is organized by SMAI-SIGMA one of the activity groups of the SMAI (French equivalent of the SIAM).


    October 31st to November 4th, 2016


    CIRM, Marseille

    Plenary Speakers

    Rachid Ait-Haddou (Osaka) Pierre Alliez (INRIA) Jean-Daniel Boissonnat (INRIA) Bernardo De la Calle (Madrid) Antonin Chambolle (CNRS and Polytechnique) Jalal Fadili (Caen) Mario Figueiredo (Lisboa) Daniel Kressner (EPF Lausanne) Arno Kuijlaars (Leuven) Gitta Kuttyniok (Berlin) Juliette Leblond (INRIA Sophia) Carla Manni (Rome) Konstantin Mischaikow (Rutgers University) Anthony Nouy (Nantes) Miguel Pinar (Granada) Christoph Schnorr (Heidelberg) Christian Sohler (Dortmund) Gabriele Steidl (Kaiserslautern) Georg Umlauf (Konstanz) Holger Wendland (Oxford)

    Scientific committee

    Albert Cohen (Paris 6) Olivier Gibaru (ENSAM) Christian Gout (Rouen) Quentin Mérigot (CNRS and Paris-Dauphine) Eric Nyiri (ENSAM) Valérie Perrier (Grenoble)

    Organizing committee

    Bernhard Beckermann (Lille 1) Frédéric Chazal (INRIA) Tom Lyche (Oslo) Marie-Laurence Mazure (Grenoble) Gabriel Peyré (CNRS and Paris-Dauphine, France)

    Pre-registration: free but mandatory

    Register online here.


    [not yet available]


    [not yet available]

    Friday afternoon dedicated to Claude Shannon (in French)

    A l'occasion du centenaire de la naissance de Claude Shannon, le groupe SIGMA de la SMAI organise le Vendredi 4 Novembre après midi au CIRM une après midi d'exposés grand public autour de l'oeuvre scientifique de Claude Shannon, de la théorie de l'information et de ses applications.

    14:00-14:30 : Caroline Chaux (CNRS et Univ. Marseille) : l'échantillonnage
    14:30-15:00 : Gabriel Peyré (CNRS et Univ. Paris-Dauphine): la compression de données
    Pause café
    15:30-16:00 : Christophe Ritzenthaler (Univ. Rennes) : les codes correcteurs
    16:00-16:30 : Jalal Fadili (ENSICaen): l'échantillonnage compressé


    [not yet available]


    The CIRM is located in a nice place, close to some of the famous "Calanques de Marseille", beautiful typical creeks. There will be no talks on Wednesday afternoon to give the participants an opportunity to enjoy the surroundings. More details about how to get there can be found on the web site of the CIRM.

    The conference includes breakfasts, lunches and diners free of charge from Sunday evening to Friday noon. Transportation is left at the charge of the participants.

    There is only a limited number of single and double hotel rooms at the CIRM (from Sunday evening to Friday morning). Those rooms are free of charge. People who will register late may not obtain one of them, and will have to book an hotel room outside the CIRM on their own. We thus advise you to register early.



  • Geo-Sci-Info

    General International conferences on distances


    General international conferences on distances were:

    1992: Distancia, org. by Le Calve in Rennes, France
    Proc. published by Universite de Bretagne, 1992

    1994: Discrete Metric Spaces, org. by W.Deuber and M.Deza in Bielefeld, Germany.
    Proc. European Journal of Combinatorics, Special Issue of
    Discrete Metric Spaces, 17-2,3 (1996)

    1996: Discrete Metric Spaces II, org. by W.Deuber and M.Deza in Lyon, France.
    Proc. Discrete Mathematics 192,1-3 (1998)

    1998: Discrete Metric Spaces III, org. by M.Deza in CIRM, France
    Proc. European Journal of Combinatorics, Special Issue of
    Discrete Metric Spacesâ, 21-6 (2000)

    2012: Mathematics of Distances and Applications, org. by M.Deza, M.Petitjean and
    K.Markov in Varna, Bulgaria
    Proc. were published as a book

    2013: Distance Geometry and Applications - DGA'2013, org. by C.Lavor, A.Mucherino et al.
    in Manaus, Brazil
    Proc. in Special Issue of Discrete Appl. Math. 2014

    2013: GSI2013 - Geometric Science of Information
    , Paris, France.
    SESSION: Discrete Metric Spaces

    2014: Many Faces of Distances, workshop, org. by C.Lavor, M.Firer et el.
    in Campinas, Brazil

  • Day Conference - Institut Henri Poincaré - 14 Sept. 2016


    Bandeau duhem.jpg


    Pierre Duhem (1861-1916) et ses contemporains
    Institut Henri Poincaré, 14 Septembre 2016
    Amphithéâtre Hermite
    organisée par Hervé Le Ferrand (Dijon) - Laurent Mazliak (Paris)


    9h30 Accueil-Présentation
    9h45-10h30 Nicolas Wipf (Metz) « Le jeune Duhem: formation et controverses »
    10h30-11h15 Antonietta Demuro - Rossana Tazzioli (Lille) « Les premières recherches en hydrodynamique à Lille »
    11h30-12h15 Jean-François Stoffel (Bruxelles) « Duhem à travers sa correspondance : quelques surprises et quelques confirmations »
    12h15-13h00 Claude Bardos (Paris) « Pierre Duhem et Jacques Hadamard à Bordeaux »


    14h30-15h15 Stefano Bordoni (Bologne) « Pierre Duhem et la thermodynamique »
    15h15-16h00 Anastasios Brenner (Montpellier) « Pierre Duhem épistémologue »
    16h00-16h45 Cédric Chandelier (Aix-Marseille) « Pierre Duhem historien des sciences »
    16h45-17h30 Discussion générale

    Pour tout renseignement : laurent.mazliak [ at ]

    Résumés des conférences

    Claude Bardos (laboratoire Jacques Louis Lions, Université Pierre et Marie Curie)
    « Pierre Duhem et Jacques Hadamard à Bordeaux : de l’amitié à l’éclosion de la théorie moderne des équations aux dérivées partielles »
    Pour cet exposé je dispose avant tout de deux éléments. D’une part une bonne connaissance de l’œuvre d’Hadamard sur les équations aux dérivées partielles et d’autre part de l’excellent livre de Mazya et Shaposhnikova également sur Hadamard. Je me propose donc de montrer comment les travaux de Paul Duhem qui se concrétisent par exemple dans le livre Hydrodynamique acoustique , élasticité , acoustique (Hermann, Paris, 1891) ont pu dans la période où ils étaient tous les deux à Bordeaux, conduire Jacques Hadamard a élaborer des concepts qui motiveront les recherches d’au moins trois générations de mathématiciens. Stefano Bordoni (Scuola di Farmacia, Biotecnologie e Scienze motorie, Université de Bologne)
    « Pierre Duhem et la thermodynamique »
    Je me concentrerai sur la thermodynamique généralisée de Duhem ou, si vous préférez, sa mécanique généralisée ou Energétique. Duhem a toujours mentionné les savants qui l’ont précédé dans la recherche d’une théorie physique générale : d’abord Rudolf Clausius, et ensuite François Massieu, Joshia Willard Gibbs, Hermann von Helmholtz, Arthur von Oettingen … Il a aussi reconnu le rôle joué par Lagrange dans le développement d’une physique qui pouvait se libérer des modèles mécaniques microscopiques. Je donc voudrais présenter Duhem comme point d’arrivée d’une tradition : je me concentrerai sur les premières étapes de Duhem thermodynamicien, sur les années qui vont de 1892 à 1896, pour retracer quelques influences et pour souligner les nouveautés.
    En 1894, dans la troisième partie de son « Commentaire aux principes de la Thermodynamique » il étonna probablement les lecteurs en raison de la référence à une interprétation aristotélicienne du mot «mouvement»: non seulement le mouvement était considéré comme un processus cinématique, mais comme une transformation en général [Duhem 1894a, p. 222]. Pour sa thermodynamique généralisée, Duhem choisit une généralisation du lexique mécanique traditionnel. L’équilibre thermique d’un système physique était perturbé par des actions qui étaient la généralisation du frottement et de la viscosité mécaniques.. Les résistances généralisées lui permettaient de réinterpréter l'entropie [Duhem 1894a, pp. 223-4 and 229] et de mettre en place une nouvelle physique généralisée qui prétendait avoir l’ampleur de la philosophie naturelle d’Aristote. En 1896, dans le livre Théorie thermodynamique de la viscosité, du frottement et des faux équilibres chimiques, Duhem essaya de construire une structure mathématique aussi générale que souple, qui pourrait s'adapter aux particularités des systèmes spécifiques, et pourrait être progressivement élargie afin de rendre compte de phénomènes d'une complexité croissante.
    Les équations générales contenaient aussi bien les termes d'inertie que deux termes dissipatifs. Quand il laissait tomber les termes de dissipation, une réinterprétation de la mécanique traditionnelle émergeait. Quand il laissait tomber les termes d'inertie, certaines simplifications mathématiques le conduisaient à une nouvelle mécanique des processus chimiques explosifs [Duhem 1896, pp. 128-131]. Une structure mathématique flexible pouvait inclure à la fois la science antique et moderne, la mécanique classique et une nouvelle mécanique chimique qui pouvait être considérée comme une réinterprétation de la philosophie naturelle d'Aristote [Duhem 1896, p. 205]. Anastasios Brenner (C.R.I.S.E.S., Université Montpellier 3)
    « Pierre Duhem épistémologue »
    La réflexion philosophique de Duhem est suscitée par la crise qui secoue la physique au tournant du XXe siècle : la constitution d’une thermodynamique indépendante de la mécanique. Il fait remonter l’ébauche de sa doctrine à un défi : présenter la thermodynamique de façon rigoureuse et intelligible. Les concepts et les principes de cette branche de la physique se distinguent par leur généralité et leur abstraction. Duhem se donne alors pour tâche de « reprendre jusqu’en ses fondements l’analyse de la méthode par laquelle se peut développer la théorie physique ». Ses écrits philosophiques visent à fournir une explication et une justification de cette démarche. Duhem est conduit à rejeter une conception empiriste naïve ; c’est le sens de sa critique de la méthode newtonienne et de l’expérience cruciale. Les grands principes de la physique ne peuvent plus être présentés comme le résultat direct de la raison commune ou de l’expérience ordinaire. Ce sont des conventions, qui manifestent le libre choix du théoricien. Cette affirmation fait écho à la position énoncée simultanément par Poincaré au sujet des hypothèses de la géométrie. La convergence entre les deux savants ne manque pas de frapper leurs contemporains, ouvrant la voie à une doctrine épistémologique originale.
    Il ne s’agit pas d’être conduit au scepticisme, et l’œuvre duhémienne se déploie comme une tentative d’élucidation : l’intégration de la théorie et de l’expérience, l’évolution des concepts ainsi que le concours de valeurs rationnelles enclenchent un mouvement lent et subreptice mais indéniable. Selon Duhem la représentation que procure la théorie aboutit à une organisation des lois, à une classification. Au cours du temps, les classifications sont améliorées ; elles deviennent de plus en plus naturelles. Les exigences d’exactitude, de cohérence et de puissance prédictive fournissent une justification rationnelle du choix du scientifique. Cédric Chandelier (C.E.P.E.R.C., Université d'Aix-Marseille)
    « Pierre Duhem historien des sciences »
    Les théories physiques évoluent, d’après Pierre Duhem, vers une forme parfaite qu’elles n’atteindront jamais. C’est dans cette tension vers une « classification naturelle » que réside ce qui distingue l’épistémologie duhémienne du conventionnalisme. Duhem, pas plus que Poincaré, ne renonce au nom de la liberté à la valeur ontologique du savoir positif, et l’histoire joue un rôle crucial dans la reconnaissance, au cœur de la science, d’une aspiration qui la dépasse. Qu’aucune théorie ne puisse être infirmée par l’expérience ne la rend pas arbitraire vis-à-vis des faits empiriques : le but du physicien selon Duhem est la représentation ordonnée des lois expérimentales ; et la recherche scientifique de l’harmonie de ces lois trouve sa source dans une croyance de métaphysicien. En dépit du mur indépassable que l’épistémologue place entre la méthode positive et l’affirmation métaphysique, l’historien des sciences prend acte de cette affirmation, par laquelle le savant transgresse l’infranchissable. Et si Duhem s’en tient explicitement au schisme de l’âme entre corps et conscience, la liberté qu’il prend vis-à-vis de sa propre doctrine permet de mesurer l’erreur qu’il y a à réduire la physique du croyant au dogme catholique. L’histoire des sciences, chez Duhem, ne peut être cloisonnée de l’histoire des cosmologies : la « preuve par analogie », qui fait du mouvement de la physique théorique une métaphore de celui de la foi, n’a certes pas la valeur contraignante d’une démonstration logique, mais de même que l’expérience peut conduire sans nécessité à la préférence d’une théorie plus globale, rien n’empêche de franchir l’indémontrable en transgressant allégoriquement le sens positif de l’histoire. C’est ce que Duhem fait lui-même en trouvant dans la thermodynamique une image de la cosmologie péripatéticienne. Antonietta Demuro, Rossana Tazzioli (Laboratoire Painlevé, Université Lille 1)
    « Les premières recherches en hydrodynamique à Lille»
    Pierre Duhem a passé à Lille les premières années de sa carrière académique, de 1887 à 1893. Les sujets de ses cours donnés à l'Université de Lille concernent l'hydrodynamique, l'électricité, le magnétisme, la thermodynamiuque, et l'optique. Le but de notre exposé est de contextualiser les premières recherches de Duhem en hydrodynamiques pas seulement au point de vue scientifique et institutionnel, mais aussi par rapport à ses enseignements, à l'intéraction avec ses collègues et à son engagement vis à vis des élèves. Jean-François Stoffel (Bruxelles)
    « Duhem à travers sa correspondance : quelques surprises et quelques confirmations »
    Le Fonds Pierre Duhem de l’Institut de France conserve la correspondance, essentiellement passive, professionnelle (2.961 lettres échangées avec 542 correspondants de 17 nationalités différentes) et personnelle (1.049 lettres adressées à sa fille Hélène) de notre savant. Cette mine d’informations permet de préciser sa biographie intellectuelle (par ex. les raisons de son maintien loin de la capitale) et de reconstituer son véritable réseau de relations, souvent éloigné de celui qu’on pouvait imaginer. Il apparaît en effet que certains auteurs, dont le nom n’apparaît que très occasionnellement sous la plume de notre penseur, voire pas du tout (par ex. M. Blondel, B. Lacome ou P. Mansion), ont, en fait, particulièrement stimulé sa pensée, quand d’autres, qui paraissaient sembler intellectuellement proches de lui (par ex. J. Bulliot, le destinataire d’une célèbre lettre encore souvent rééditée), ne le sont guère et attirent, de sa part, un jugement pour le moins sévère. C’est dire si les informations contenues dans cette correspondance, bien que disparates et souvent difficiles à exploiter, sont en fait irremplaçables. Nicolas Wipf (Lycée Fabert, Metz)
    « Le jeune Duhem: formation et controverses »
    En suivant le parcours du jeune Duhem, des bancs du collège à son entrée à l’Université, nous verrons apparaître les prémisses de l’œuvre d’un physicien doué et ambitieux, d’un épistémologue ancré dans ses convictions et d’un homme au caractère parfois ombrageux.
    Duhem intègre le Collège Stanislas en 1872, un établissement au sein duquel il retrouve les valeurs catholiques et conservatrices inculquées par ses parents. Excellent élève, il s’initie très tôt aux sciences physiques grâce à son professeur Jules Moutier : « c’est ce maître qui fit germer en nous l’admiration pour la théorie physique et le désir de contribuer à son progrès ». La lecture de travaux récents publiés par Gibbs et Helmholtz l’oriente alors rapidement vers son futur programme de recherche : l’élaboration d’une thermodynamique générale.
    Premier de promotion à l’Ecole Normale Supérieure (1882 – 1887), il présente dès 1884 sa propre théorie du « potentiel thermodynamique » comme thèse de physique mathématique. La commission chargée d’évaluer ce travail considère toutefois que celui-ci n’est « pas de nature à être soutenu comme thèse devant la Faculté des Sciences de Paris ». Ce refus s’explique-t-il simplement par le manque d’expérience de l’impétueux normalien ? Ne serait-ce pas plutôt lié au fait que Duhem y critique vivement la théorie défendue par Berthelot, figure influente de la chimie française et homme politique de premier ordre durant la Troisième République ?
    Nommé à l’Université de Lille en 1887, Duhem espère que cette affectation précède un retour rapide à Paris… Mais il passera finalement l’ensemble de sa carrière universitaire en province (après un départ rocambolesque de Lille en 1893 et un court passage à Rennes, il finira sa carrière à Bordeaux). Selon lui, les « potentats » de la communauté scientifique, Berthelot en tête, ont tout fait pour « lui barre[r] la route de Paris ».

  • 11-12th October - INRIA Paris Research Center


    CAVALIERI Workshop on Optimization and Optimal Transport in Imaging


    Dates: 11th to 12th October
    Location: Salle Jacques-Louis Lions 2 at INRIA Paris Research Center



    Claire Boyer, LSTA, UPMC Nicolas Bonneel, Liris, Université Claude-Bernard Lyon 1 Elsa Cazelles, IMB, Université de Bordeaux Lénaïc Chizat, CEREMADE, Université Paris Dauphine Emilie Chouzenoux, Laboratoire Gaspard Monge, Univ. Paris-Est Quentin Denoyelle, CEREMADE, Université Paris Dauphine Alexandre Gramfort, Telecom ParisTech Franck Iutzeler, LJK, Université Grenoble Alpes Bruno Lévy, ALICE, Inria Nancy Grand-Est / Loria Klas Modin, Chalmers Univ. of Technology Clarice Poon, DAMTP, University of Cambridge Carola-Bibiane Schönlieb, DAMTP, University of Cambridge Pauline Tan, DOTA, ONERA Benedikt Wirth, Institute for Computational and Applied Mathematics, Universität Münster

    While optimization has been playing a key role in signal and image processing for many decades, the signal and image processing community has made tremendous progress in the last ten years by adopting proximal methods. That breakthrough paved the way to large scale image processing in inverse problems (compressive sensing, deconvolution, inpainting.) as well as new and more involved modalities.
    In the meantime, optimal transport has evolved from a purely theoretical field into a new and exciting challenge for numericians, raising specific issues in terms of optimization and numerical analysis (entropic regularization, degenerate elliptic schemes.).
    The goal of this workshop is to bring together confirmed and upcoming experts in both fields, exchanging on their most recent advances and problems.


    Charles-Alban Deledalle (IMB) Charles Dossal (IMB) Vincent Duval (INRIA) Nicolas Papadakis (IMB) Julien Rabin (GREYC) François-Xavier Vialard (CEREMADE/INRIA)

  • 3rd conference on Geometric Science of Information - 1st October- 31st December 2017





    First announcement and call for papers
    As for GSI’13 and GSI’15, the objective of this SEE GSI’17 conference, hosted in Paris,
    is to bring together pure/applied mathematicians and engineers, with common interest for
    Geometric tools and their applications for Information analysis.
    It emphasizes an active participation of young researchers to discuss emerging areas of
    collaborative research on “Geometric Science of Information and their Applications”.
    Current and ongoing uses of Information Geometry Manifolds in applied mathematics are
    the following: Advanced Signal/Image/Video Processing, Complex Data Modeling and
    Analysis, Information Ranking and Retrieval, Coding, Cognitive Systems, Optimal Control,
    Statistics on Manifolds, Topology/Machine/Deep Learning, Artificial Intelligence,
    Speech/sound recognition, natural language treatment, Big Data Analytics, etc., which are
    substantially relevant for industry.
    The Conference will be therefore held in areas of priority/focused themes and topics of
    mutual interest with the aim to:

    Provide an overview on the most recent state-of-the-art Exchange mathematical information/knowledge/expertise in the area Identify research areas/applications for future collaboration Identify academic & industry labs expertise for further collaboration

    This conference will be an interdisciplinary event and will unify skills from Geometry,
    Probability and Information Theory.
    The conference proceedings are published in Springer's Lecture Note in Computer
    Science (LNCS) series.

    Important Dates:
    Main deadlines are the following:

    Deadline for 8 pages SPRINGER LNCS format: 3 rd of April 2017 Notification of acceptance: 12 th of June 2017 Final paper submission: 31 st of July 2017
    Paper templates (Latex, Word) and Guideline on GSI’17 website at “Author Instructions”:

    Provisional topics of Special Sessions:
    The following Special Sessions have been identified but will not be limited to:

    Statistics on non-linear data Shape Space Optimal Transport & Applications I (Data Science and Economics) Optimal Transport & Applications II (Signal and Image Processing) Topology and statistical learning Statistical Manifold & Hessian Information Geometry Information Structure in Neuroscience Geometric Robotics & Tracking Geometric Mechanics & Robotics Stochastic Geometric Mechanics & Lie Group Thermodynamics Probability on Riemannian Manifolds Divergence Geometry Geometric Deep Learning First and second-order Optimization on Statistical Manifolds Non-parametric Information Geometry Geometry of quantum states Optimization on Manifold Computational Information Geometry Probability Density Estimation Geometry of Tensor-Valued Data Geometry and Inverse Problems Geometry in Vision, Learning and Dynamical Systems Lie Groups and Wavelets Geometry of metric measure spacesProvisional program of Invited Speakers: Geometry and Telecom Geodesic Methods with Constraints

    Provisional program of Invited Speakers:
    3 keynote speakers’ talks will open each day. An Invited Honorary speaker will give a talk
    at the end of 1 st day and a Guest Honorary speaker will close the conference.

    Alan Turing Institute .png

  • April 17-21, 2017 - Amirkabir university of Technology - Tehran - Iran



    Preleminary organization announcement

    Organization of the second edition of the workshop BigDataLifeScience has started.

    The preliminary program is:

    two days of scientific work (April 17-18, 2017) one day workshops (April 19, 2017) for CNRS-AUT common projects definition one day workshop and visit to Shiraz (April 20) and one day workshop and visit to Ispahan (April 21)

    A long term objective that we are focusing is the creation of common
    working projects and perhaps a common CNRS-AUT research center (LIA).

    Conference general chair: Ali Mohammad-Djafari
    Laboratoire des signaux et systèmes (L2S), CNRS-CentraleSupélec-Univ. Paris Saclay, Gif-sur-Yvette, France Executive chair: Mina Aminghafari
    Faculty of Mathematics and Computer Science of AUT Local organisers:
    Adel Mohammadpour, Mathematics Dept. AUT
    Mina Aminghafari, Mathematics Dept. AUT

  • Centre International de Rencontres Mathématiques (CIRM) - Marseille/Luminy - 15 - 19 may 2017


    19ème conférence en Géométrie stochastique, stéréologie et analyse d'images
    Centre International de Rencontres Mathématiques (CIRM), à Marseille/Luminy du 15 au 19 mai 2017.


    Cette conférence est la 19ème d'une série de workshops intitulés Stochastic Geometry, Stereology and Image Analysis (SGSIA) qui ont été organisés tous les deux ans depuis 1981. L'événement qui a lieu pour la première fois en France constitue la principale occasion de promouvoir les avancées récentes en géométrie stochastique, statistique spatiale, géométrie convexe et intégrale, stéréologie et analyse d'image. Il est simultanément le rassemblement annuel de tous les membres du groupement de recherche Géométrie Stochastique (GeoSto, GDR 3477) qui est financé par le CNRS depuis 2012. Le programme scientifique devrait couvrir tous les aspects des thèmes principaux tout en s'aventurant occasionnellement un peu au-delà de leurs frontières. L'emploi du temps permettra naturellement les discussions et interactions entre les participants.

    Liens vers les précédents workshops SGSIA:

    Liens vers les précédentes conférences GeoSto:

    Comité scientifique

    François Baccelli (INRIA Paris et University of Austin) Wilfrid Kendall (University of Warwick) Marie-Colette van Lieshout (CWI Amsterdam) Claudia Redenbach (Kaiserlautern Universität) Joseph E. Yukich (Lehigh University)

    Comité d'organisation

    Pierre Calka (Université de Rouen) Jean-François Coeurjolly (Université du Québec à Montréal) David Coupier (Université Lille 1) Anne Estrade (Université Paris Descartes) Ilya Molchanov (University of Bern)

    Conférenciers invités

    Adrian Baddeley (University of Western Australia) Antonio Cuevas (Universidad Autonoma de Madrid) Dominique Jeulin (Mines ParisTech) Rolf Schneider (Universitat Freiburg) Gunter Last (Karlsruhe Institute of Technology) Jean-Michel Morel (ENS Cachan) Giovanni Peccati (Luxembourg University) Perla Sousi (University of Cambridge) Martina Zahle (Jena Universitat) Johanna Ziegel (University of Bern)

  • Friday 2.PM weekly seminar - Room 1016 - Bâtiment Sophie Germain, University Paris-7 - France


    Page Web officielle

    Séminaire de géométrie et physique mathématique

    organisé par Serguei Barannikov, Daniel Bennequin, Christian Brouder,
    Frédéric Hélein et Volodya Roubtsov

    Bâtiment Sophie Germain, Paris 13ème
    (voir le plan d'accès) Salle 1016
    Année précédente (2015-2016)

    Prochaine scéance Année 2015-2016:

    Vendredi 28 octobre 2016, 14 h
    salle 1016 :
    Charles-Michel Marle,

    Les travaux de Jean-Marie Souriau en mécanique statistique et en thermodynamique, et en particulier sa généralisation de la notion d'état de Gibbs aux actions hamiltoniennes d'un groupe de Lie
    Résumé : Après un bref rappel des principes de la mécanique statistique classique et de la notion d'état de Gibbs, et la présentation de quelques résultats qui s'en déduisent (équation d'état d'un gaz parfait monoatomique, lois de distribution de l'impulsion de Maxwell-Boltzmann pour un gaz non relativiste et de Maxwell-Jüttner pour un gaz relativiste, loi de Dulong et Petit pour la chaleur spécifique des solides), je présenterai la généralisation de la notion d'état de Gibbs aux actions hamiltoniennes d'un groupe de Lie sur une variété symplectique, due à Jean-Marie Souriau. La notion d'état de Gibbs usuelle apparaît comme un cas particulier dans lequel le groupe de Lie, de dimension 1, est le groupe des translations temporelles. Mon exposé sera une préparation à celui de Frédéric Barbaresco qui aura lieu le 25 novembre 2016.

    Vendredi 4 novembre 2016, 14 h
    salle 1016 :
    Juan Pablo Vigneaux

    Cohomologie de l'information
    Résumé : Baudot et Bennequin [1] ont introduit une cohomologie adaptée à la théorie de l'information. Cette cohomologie suit les constructions générales décrits dans le SGA IV (théorie des topos) ; le topos de l'information est le topos de préfaisceaux sur un site définie par des variables aléatoires.

    On peut définir une famille des faisceaux (F_q) (pour (q>0)), tels que l'entropie de Shannon génère le groupe (H^1(F_1)) et les entropies de Tsallis génèrent (H^1(F_q)), pour (q) différent de 1. Autres fonctions d'information apparaissent aussi comme cocycles et la théorie s'étend au cas quantique.

    L'axiomatisation usuelle de l'entropie, due à Shannon, peut être interprété dans le cadre d'extensions (des faisceaux) d'algèbres et correspond au cas scindée. Cela suggère des interprétations possibles pour les classes d'ordre supérieur.

    [1] Baudot, P.; Bennequin, D. The Homological Nature of Entropy. Entropy 2015, 17, 3253-3318.

    à suivre ...

    Vendredi 18 novembre 2016, 14 h

    Pas de séminaire

    Vendredi 25 novembre 2016, 14 h
    salle 1016 :
    Frédéric Barbaresco
    Groupe Thalès

    Modèle de la "Thermodynamique des groupes de Lie" de Jean-Marie Souriau: cohomologie symplectique de l'Information et métrique de Fisher-Souriau
    Résumé : résumé détaillé
    Voir aussi la prépublication : Geometric Theory of Heat from Souriau Lie Groups Thermodynamics and Koszul Hessian Geometry: Applications in Information Geometry for Exponential Families et les références dans le numéro spécial de Differential Geometrical Theory of Statistics, notament l'article de Charles-Michel Marles

    Vendredi 8 décembre 2016, 14 h
    salle 1016 :
    Tilmann Wurzbacher
    Université de Lorraine, Metz

    Applications moment en géométrie multisymplectique
    Résumé :

    Séances précédentes :

    Vendredi 14 octobre 2016, 14 h
    salle 1016 :
    Penka Vasileva Giorgieva

    Théorie de Gromov-Witten réelle
    Résumé :

    Vendredi 7 octobre 2016, 14 h
    salle 1016 :
    Vincent Caudrelier
    Université de Leeds (Royaume-Uni)

    Lagrangian and Hamiltonian structures in an integrable hierarchy
    Résumé : The classical and quantum versions of the R matrix are the cornerstones in classical and quantum integrable systems, typically formulated in 1+1 dimensions. They are the heart of the theory developed by the Fields medallist V. Drinfeld. However, they traditionally concentrate all the attention on only one of the independent variables: the space one while time evolution is encoded more or less trivially. The latter point is in fact deeply related to the boundary conditions imposed on the system. A big success of the theory of classical integrable systems is the systematic Hamiltonian formulation of the corresponding PDEs. The essential object capturing the Hamiltonian properties (infinite number of conserved quantities, etc) is the so-called classical r-matrix. Motivated originally by the question of integrability of certain field theories in the presence of defects, we will show how a dual Hamiltonian structure naturally emerges which gives a fully fledged r-matrix structure to the time variable. This is inspired and related to the notion of covariant field theory. The interplay between the standard classical r-matrix structure and the dual one raises many questions and begs for a "multisymplectic r-matrix theory". Time permitting, we will speculate on other related open questions: quantization and out-of-equilibrium systems.

  • Conference for Shannon 100th birthday - IHP - 26- 28 october 2016 - Paris - France




    Vendredi 28 octobre 2016

    Frank Nielsen (École Polytechnique)
    The dual geometry of Shannon information and its applications
    Abstract: In information geometry, the negative Shannon entropy, called the Shannon information, is a strictly convex and differentiable function that induces a dually flat manifold structure equipped with the Kullback- Leibler divergence. In this talk, I review the concept of dual geometries, introduce the dual space of spheres, and describe the role of divergences in information theory, statistics, pattern recognition and machine learning.
    Frank Nielsen received his PhD (1996) and his habilitation (2006) on computational geometry from the University of Nice-Sophia Antipolis, France. After the French national service, he joined Sony CSL (Japan) in 1997. He is currently professor in the computer science department of École Polytechnique (France). He co- organizes with Frédéric Barbaresco (Thales) the biannual Geometric Sciences of Information (GSI) conference, and is an associate editor of the Springer Journal of Mathematical Imaging and Vision and of MDPI Entropy.

    Ruediger Urbank (EPFL)
    Happy Numbers: 68 Years of Coding, 6² + 8² = 100 Years of Shannon, 1² + 0² + 0² = 1 Goal
    Abstract: This year, we celebrate Shannon’s 100th birthday and it has been 68 years since he laid the foundations of communications. To realize his number 1 goal or error free communication we use error correcting codes. Every time we make a call, connect to WiFi, download a movie, or store a file, they help us get things right. The journey began with codes based on algebraic structures such as Reed-Muller and Reed- Solomon codes. Then lattices helped convey continuous-valued signals. Slowly, deterministic codes made way for random sparse graphs codes with low-complexity message-passing decoding, such as Turbo codes and LDPC codes. The new millennium brought us Polar codes that use the chain rule of mutual information to achieve capacity and spatially-coupled codes that exploit the physical mechanism that makes crystals grow to simultaneously achieve the capacity of a large family of communication channels. Recently, the story has come full circle, and the symmetry inherent in algebraic constructions has brought the focus back on Reed-Muller codes. I will describe how ideas from such diverse areas as abstract algebra, number theory, probability, information theory, and physics slowly made it from the blackboard into products, and outline the main challenges that we face today.
    Ruediger Urbanke (Phd, WashU, St. Louis, 1995) has been obsessed with questions in coding theory for the past 20 years. Fortunately his progress has been slow so that there are many problems left for him for the next 20 years. He likes sabbaticals and owns more bicycles than can be rationally justified. Before joining EPFL in 1999, he enjoyed working at Bell Labs (Murray Hill) at the Mathematics of Communications Group.

    Robert G. GALLAGER (MIT)
    Claude Shannon: His life, modus operandi, and impact

    Cédric Villani (Directeur de l’Institut Henri Poincaré)
    Discours de cloture


  • December 7th 2016 - IRISA INRIA Rennes France




    Distance Geometry Day in Rennes
    December 7th, 2016

    Distance Geometry (DG) is a consolidated research area, where mathematics and computer science are at its foundation. Classical applications of DG include the one of identifying the 3D conformations of biological molecules, the problem of localizing sensors in a given network, and the clock synchronization problem. Morever, recent research activities have been showing that there are several other applications that can be actually faced by DG. Examples are human motion adaptation, crowd simulations and virtual camera control.

    This DG Day (DGD) has as main purpose to bring together researchers working on different aspects of the DG and on some of its applications. The talks will give either an overview of the current research on DG solution methods, or describe particular applications where the DG approach can bring to the discovery of new interesting scientific results.

    DGD16 date and venue

    The DGD16 will be held on December 7th, 2016, at IRISA, INRIA Rennes, in Les Minquiers room.

    Invitation-based scientific program

    9:30 - 9:50
    Registration and Coffee

    9:50 - 10:00
    Opening, DGD16 Chair.

    10:00 - 10:50
    Mathematical Gems in Distance Geometry
    Leo Liberti, CNRS-LIX, École Polytechnique, Palaiseau
    (joint work with: C. Lavor)
    Distance geometry focuses on the concept of distance rather than points and lines. Its fundamental problem asks to draw a weighted graph in a given K-dimensional Euclidean space, so that each edge is drawn as a segment with length equal to the weight, and it has applications to many fields of science and engineering (e.g. protein folding, wireless networks, robotic control, nanostructures and more). Distance geometry results are scattered throughout the whole history of mathematics starting with the Greeks. I will present some of those I find most beautiful, from a selection including: Heron's theorem, Cauchy's theorem about rigidity of convex polyhedra, Goedel's theorem about realizability on a sphere, Schoenberg's theorem linking Euclidean Distance Matrices and Positive Semidefinite Matrices, and a surprising theorem of Johnson and Lindenstrauss about approximately projecting realizations from very high dimensional spaces.

    10:50 - 11:20
    Practical Implementation Considerations of Interval Branch-and-Prune for Protein Structure Determination
    Bradley Worley, Institut Pasteur, Paris
    (joint work with: T. Malliavin, B. Bardiaux, M. Nilges, C. Lavor, L. Liberti)
    The interval Branch and Prune (iBP) algorithm for obtaining solutions to the interval Discretizable Molecular Distance Geometry Problem (iDMDGP) has proven itself as a powerful method for molecular structure determination. However, substantial obstacles still must be overcome before iBP may be employed as a tractable general-purpose alternative to exist- ing structure determination algorithms. This work demonstrates how careful choice of data structures and mathematical frameworks leads to dramatic improvements in the performance of iBP in the specific case of protein structure determination. Moreover, it demonstrates how "soft" pruning of protein conformational space using interval-derived pseudo-potential energy functions may be utilized in lieu of "hard" pruning, which can become intolerant to otherwise acceptable minor geometric inconsistencies in molecular structures.

    11:20 - 11:50
    Feasibility Check for the Distance Geometry Problem: an Application to Molecular Conformations
    Rosa Figueiredo, LIA, University of Avignon
    (joint work with: A. Agra, C. Lavor, N. Maculan, A. Pereira, C. Requejo)
    The distance geometry problem (DGP) consists in finding an embedding in a metric space of a given weighted undirected graph such that for each edge in the graph, the corresponding distance in the embedding belongs to a given distance interval. We discuss the relationship between the existence of a graph embedding in a Euclidean space and the existence of a graph embedding in a lattice. Different approaches, including two integer programming (IP) models and a constraint programming (CP) approach, are presented to test the feasibility of the DGP. The two IP models are improved with the inclusion of valid inequalities, and the CP approach is improved using an algorithm to perform a domain reduction. The main motivation for this work is to derive new pruning devices within branch-and-prune algorithms for instances occurring in real applications related to determination of molecular conformations, which is a particular case of the DGP. A computational study based on a set of small-sized instances from molecular conformations is reported. This study compares the running times of the different approaches to check feasibility.

    11:50 - 14:00
    Lunch break, light meal offered to invited speakers and scientific committee.

    14:00 - 14:50
    The Interplay between Graph Rigidity and Multi-Robot Coordination
    Paolo Robuffo Giordano, INRIA Rennes
    Graph theory has a predominant role in the field of multi-robot coordination problems (spanning, e.g., distributed formation control and estimation schemes). Indeed, graphs are a convenient (combinatorial) abstraction for representing the various sensing/communication constraints among pairs of robots in the environments. Vertexes represent robots, and edges the possibility for a robot to measure/communicate with another robot in the group.
    In this context, the notion of graph rigidity is gaining popularity since rigidity of a multi-robot "framework" (i.e., formation) has proven to be a necessary condition for the solution of many formation control/cooperative localization problems. Moreover, exploiting the tools of algebraic graph theory, one can associate combinatorial graph properties, such as rigidity, to some suitable spectral properties (i.e., eigenvalues) of associated matrixes. This spectral interpretation of graph-related properties makes it possible to ultimately design simple "gradient-like" controllers for the robot group able to solve formation control and localization problems in a decentralized way.
    This talk will review the concepts of graph rigidity in the context of multi-robot applications, and present some recent results obtained with a team of quadrotor UAVs (drones) used as robotics platforms.

    14:50 - 15:20
    Regulating Distance in Human Movement Coordination
    Laurentius Meerhoff, IRISA Rennes
    (joint work with: J. Pettré, R. Kulpa, A. Crétual, S. Lynch, A-H. Olivier)
    The relationship between an agent (i.e., an independently decision-making entity) and its environment is the central tenet of an ecological approach to human movement. Displacement, and subsequently distance regulation, is one of the fundamental aspects of human movement. Distance needs to be regulated to avoid collision (e.g., in traffic), find a route in a complex environment (e.g., in crowd navigation) or perform coordinated behavior (e.g., in sports). In such social settings, perhaps the most prominent aspect of the environment are the other agents. Therefore, we study how collision avoidance is achieved when multiple walkers cross their trajectories. Previously it was shown that the locomotor trajectories in pairwise interactions emerge through an avoidance of risk of collision. The reciprocal interactions between these agents make the behavior complex. Moreover, many common daily life interactions encompass more than two agents, exponentially increasing the complexity. Based on animal models, it has been argued that coordination results from micro-level interactions based on simple behavioral rules which in turn lead to complex macro patterns (cf., flocking birds, schooling fish or marching on a suspension bridge). For human-to-human interactions, coordination additionally incorporates a social aspect depending on the specific situation (e.g., attractiveness of another agent). Currently, we are researching how inter-agent coordination emerges when multiple (n > 2) agents are interacting. Each agent's contribution to the inter-agent distance metrics are used to characterize the interactions. This work has implications for understanding how coordination emerges in multi-agent systems as for example crowds of people or sport teams.

    15:20 - 15:50
    Coffee break

    15:50 - 16:30
    Title to be communicated
    Marc Christie, IRISA, University of Rennes 1
    Abstract to be communicated.

    16:30 - 17:00
    Interaction-based Human Motion Analysis
    Yijun Shen, Northumbria University, Newcastle
    (joint work with: H.P.H. Shum, E.S.L. Ho)
    Traditional methods for motion analysis consider features from individual characters. However, the contextual meaning of many motions is defined by the interaction between characters. There is little success in adapting interaction-based features in evaluating interaction difference, as they are either topologically different across interactions or high dimensional. In our work, we propose a new unified framework for motion retrieval and analysis from the interaction point of view. We adapt the Earth Mover’s Distance to optimally match interaction features of different topology, which allows us to compare different classes of interactions and discover their intrinsic semantic similarity.
    We construct a comprehensive kick-boxing interaction database that is open for public for research benchmark. Experimental results show that our method outperforms existing research and aligns better with human perceived interaction similarity.

    Post DGD16 publications

    A special issue of Optimization Letters (OPTL, Springer) will collect short papers on the topics related to the DGD16. The special issue will be co-edited by the co-presidents of DGD16 committee. The call for papers can be downloaded here. All accepted papers will be published online individually, before print publication. The editorial system will be ready soon to accept submissions.

    Previous DG events

    DIMACS Workshop on Distance Geometry: Theory and Applications (DGTA16)
    Rutgers University, New Jersey, USA. F. Alizadeh and L. Liberti co-Chairs. August 2016.
    Many Faces of Distances (MFD14)
    Campinas, São Paulo, Brazil. C. Lavor and M. Ferer co-Chairs. October 2014.
    Workshop on Distance Geometry and Applications (DGA13)
    Manaus, Amazonas, Brazil. N. Maculan General Chair. June 2013.

    DGD16 Chair

    Antonio Mucherino, IRISA/INRIA and University of Rennes 1.

    DGD16 Presidents of Scientific Committee

    Antonio Mucherino, IRISA/INRIA and University of Rennes 1.
    Carlile Lavor, IMECC-UNICAMP, Campinas, São Paulo.

    Scientific Committee

    Ludovic Hoyet, INRIA Rennes Davide Frey, INRIA Rennes Sylvain Collange, INRIA Rennes Jérémy Omer, INSA, Rennes Rosa Figueiredo, University of Avignon Thérèse Malliavin, Institut Pasteur, Paris Franck Multon, University of Rennes 2

    Local organization

    Nathalie Denis, INRIA Antonio Mucherino, IRISA/INRIA and University of Rennes 1

    A special thanks

    To Mila Nobis for having designed our logo!


    The DGD16 is partially supported by CNRS (INS2I PEPS projects 2016), IRISA and INRIA Rennes.

  • Geo-Sci-Info



    Ces journées seront rythmées en deux temps:

    3 mini cours de 2h30
    Information Based Complexity, par Henryk Wozniakowski (Columbia University et Warsaw University)
    Compressive Sensing, par Holger Rauhut (RWTH Aachen University)
    QuasiMonteCarlo Methods, par Dirk Nuyens (KU Leuven) 7 exposés de 40 mn: confirmés
    Albert Cohen (Université Pierre-et-Marie Curie)
    Emmanuel Gobet (Ecole Polytechnique)
    Alexey Khartov (St-Petersburg State University)
    Peter Mathé (Weierstrass Institute, Berlin)
    Giovanni Migliorati (Université Pierre-et-Marie Curie)
    Erich Novak ((Universität Jena)

    bandau sponsor.jpg

  • Geo-Sci-Info


    Colloque International de Théories Variationnelles (CITV) 2017
    SOURIAU COLLOQUIUM - Amboise du 25/06 au 30/06/2017


    Jean-Marie Souriau ( and, born on 3 June 1922 and dead on 15 March 2012, was a French mathematician, known for works in symplectic geometry, in which he was one of the pioneers.

    He has left us not solely a master piece of scientific work through his treatises on dynamical systems, relativity and quantum mechanics but Jean-Marie Souriau –the professor and the human person– has also given us a sound philosophical vision of the world through his last book, “Grammaire de la nature”.

    Originally founded in 1956 by Jean-Marie Souriau, his doctoral students and friends, re-launched by Claude Vallée in 1996, the Colloquium entitled “Colloque International de Théories Variationnelles” (CITV) provides today an informal setting to present and discuss the state-of-the-art and the most recent findings concerning Mathematics, Physics, Mechanics and their interactions.

    Every year during a week, the CITV brings together a small group of participants hoping to work within the founder’s spirit. In marked contrast to standard Colloquia, the CITV’s style is completely informal:

    The schedule is prepared day-to-day and, if necessary, the talk durations may be adjusted under way.

    Preference is given to present ideas on the blackboard even if modern video presentations are also allowed.

    Emphasis is put on scientific maturity and creative ideas as opposed to technicalities.

    A large time is devoted to questions, discussion and exchange of ideas.

    The spectrum of topics being very broad, a special attention is paid to present advanced concepts in simple terms for people with strong scientific background but the non-specialists of the topic.

    The oral transmission of the knowledge is preferred –but not opposed– to modern communication based on paper publication.

    Epistemological talks are sometimes given in the evening and also open to accompanying persons.

    The social program is not reserved for accompanying persons but convivial interludes are scheduled in the afternoon for scientific participants sharing cultural visits and excursions with them.

    It my pleasure to announce that the 61th SOURIAU COLLOQUIUM will be held on June 25-30, 2017 at Amboise (Indre-et-Loire department, France).

    Amboise is a small and pleasant city at 2 hours from Paris by TGV and in the heart of the region of the castles of the Loire. With its castle and above all the manor of Clos-Lucé where Leonardo da Vinci spent his last days, Amboise is a cheerful reminder of what the Italian Renaissance brought to the area five centuries ago (

  • Institut Henri Poincaré, Paris, France September 4th - December 15th 2017


    General information

    Analysis in Quantum Information Theory
    Quantum Information Theory (QIT) is a rapidly developing field whose significance ranges from fundamental issues in the foundations of quantum theory to new state-of-the-art methods for secure transmission of information. The potential for powerful new methods of computation, data transmission and encryption has led to new perspectives on such entire fields as computational complexity and Shannon information theory. Work in this highly interdisciplinary and competitive area overlaps many different fields of mathematics and has widespread applications in fields like computer science and physics. The main feature of this program will be a systematic exploration of QIT via analysis (considered in a broad sense). More precisely, we will concentrate on the role of operator structures and of probabilistic tools in QIT. The operator structures of importance in QIT are in particular operator algebras, operator spaces, and operator systems. Conversely, the impact of quantum information science on these fields has been significant in the last few years. Operator algebras have a long history as a framework for quantum theory. In QIT, interactions with the environment play a major role, corresponding to the auxiliary spaces which are an essential component of operator spaces and systems. The probabilistic tools include concentration of measure, random matrix theory and large deviation theory. A related area which has probabilistic flavor, but deserves to be mentioned separately, is the asymptotic geometry of high dimensional convex bodies, which grew out of geometric functional analysis and classical convexity. At the intersection of operator algebras and (quantum) probability, there is also free probability theory, which was developed by Voiculescu in the 1990s with the aim of classifying II1 factors in von Neumann algebra theory. Free probability also turns out to play a major role in QIT, a fact which will be emphasized during the program.

    How to participate
    If you are interested in participating, you must register on the IHP website; we strongly encourage you to do so at your earliest convenience. Deadline for financial support applications: 15/03/2017.
    Structure of the semester
    On "normal" weeks, the scientific programme will be limited to 0-2 seminars per day in order to give participants time for discussions and collaborative work. Several series of educational lectures targetted at young researchers will also be organized.

    On "exceptional" weeks, some events will be organized

    04.09.17 - 08.09.17 - Summer School "Mathematical Aspects of Quantum Information"
    11.09.17 - 15.09.17 - Workshop "Operator algebras and Quantum Information Theory"
    23.10.17 - 28.10.17 - Workshop "Probabilistic techniques and Quantum Information Theory"
    11.12.17 - 15.12.17 - Conference "Quantum Information Theory"


    All the events (except the summer school) will take place at the Institut Henri Poincaré, located in downtown Paris.


    Guillaume Aubrun Benoît Collins Ion Nechita Stanislaw Szarek

    Scientific Commitee

    Patrick Hayden
    Marius Junge
    Iordanis Kerenidis
    Vern Paulsen
    Gilles Pisier
    Mary Beth Ruskai
    Andreas Winter
    Quanhua Xu

  • Geo-Sci-Info



    FLYER-PDF - Entropy 2018 conference

    Welcome from the Conference Chair

    One of the most frequently used scientific words, is the word “Entropy”. The reason is that it is related to two main scientific domains: physics and information theory. Its origin goes back to the start of physics (thermodynamics), but since Shannon, it has become related to information theory. This conference is an opportunity to bring researchers of these two communities together and create a synergy. The main topics and sessions of the conference cover:

    Physics: classical Thermodynamics and Quantum Statistical physics and Bayesian computation Geometrical science of information, topology and metrics Maximum entropy principle and inference Kullback and Bayes or information theory and Bayesian inference Entropy in action (applications)

    The inter-disciplinary nature of contributions from both theoretical and applied perspectives are very welcome, including papers addressing conceptual and methodological developments, as well as new applications of entropy and information theory.

    All accepted papers will be published in the proceedings of the conference. A selection of invited and contributed talks presented during the conference will be invited to submit an extended version of their paper for a special issue of the Journal Entropy.

    Conference Chair

    Prof. Dr. Ali Mohammad-Djafari : Research Director at CNRS, L2S, CentraleSupélec, Univ. Paris Saclay, Gif-sur-Yvette, France Ali.png

    Local Chair

    Prof. Dr. J. Miguel Rubi: Department of Condensed Matter Physics at the University of Barcelona, Spain JM_Rubi .png

    Scientific Advisory Committee Members

    Kevin Knuth : University at Albany (SUNY) Albany, NY, USA F. Barbaresco: Thales Air Systems, Limours, France Frank Nielsen École Polytechnique Palaiseau, France Mohammad Modares: University of Maryland College Park, MD, USA Pablo Piantanida: CentraleSupélec Gif-sur-Yvette, France Pierre Baudot Inserm, Marseille, France Adom Giffin: Clarkson University Potsdam, NY, USA

    Confirmed Speakers

    Ariel Caticha : University at Albany (SUNY) Albany, NY, USA David Wolpert : Santa Fe Institute, Santa Fe, NM, USA Robert Niven : University of New South Wales, Sydney, Australia Jean-Christophe Pesquet : University Paris-Saclay, Paris, France Ercan Kuruoglu : Italian National Council of Research Pisa, Italy Giovanni Pistone : Collegio Carlo Alberto Moncalieri, Italy Jean-François Bercher : ESIEE Paris, France Paul Baggenstoss :Frauhnhofer FKIE, Wachtberg, Germany Olivier Rioul: University Paris-Saclay, Paris, France Jose M. Vilar: University of the Basque Country Bilbao, Spain Signe Kjelstrup : NTNU Trondheim, Norway David Reguera : University of Barcelona, Barcelona, Spain

    Conference Secretariat

    Dr. Lucia Russo
    Ms. Yuejiao Hu
    Mr. Matthias Burkhalter
    E-mail: entropy2018 [at]
    Tel. +34 936397662

    Sponsoring Opportunities

    For information regarding sponsoring opportunities, please contact Mr. Antonio Peteira.
    E-Mail: antonio.peteira [at]
    Tel. +34 936397662

  • Geo-Sci-Info

    The Ninth International Conference on Guided Self-Organisation (GSO-2018) : Information Geometry and Statistical Physics

    March 26 - 28, 2018
    Max Planck Institute for Mathematics in the Sciences

    The goal of Guided Self-Organization (GSO) is to leverage the strengths of self-organization (i.e., its simplicity, parallelization, adaptability, robustness, scalability) while still being able to direct the outcome of the self-organizing process. GSO typically has the following features:

    (i) An increase in organization (i.e., structure and/or functionality) over time;

    (ii) Local interactions that are not explicitly guided by any external agent;

    (iii) Task-independent objectives that are combined with task-dependent constraints.

    GSO-2018 is the 9th conference in a bi-annual series on GSO. Recent research is starting to indicate that information geometry, nonequilibrium statistical physics in general, and the thermodynamics of computation in particular, all play a key role in GSO. Accordingly, a particular focus of this conference will be the interplay of those three topics as revealed by their relationship with GSO.

    The following specific topics are of special interest:

    information-driven self-organisation complex systems and networks non-equilibrium statistical physics non-extensive statistical mechanics physics of information and computation information dynamics generalised entropies generalised relative entropies alpha geometry and alpha statistics constraints and maximum entropy principle information-geometric aspects of Fokker-Planck and Kolmogorov equations

    More Information

    Conference Homepage GSO Workshop Series Keynote Speakers Tentative Program Call for Abstracts Registration

    Date and Location

    March 26 - 28, 2018
    Max Planck Institute for Mathematics in the Sciences
    Inselstraße 22
    04103 Leipzig
    see travel instructions

    Organizing Committee

    Nihat Ay MPI for Mathematics in the Sciences Leipzig (Germany) Mikhail Prokopenko University of Sydney (Australia)

    Program Committee

    Nihat Ay, MPI for Mathematics in the Sciences, Leipzig (Germany) Domenico Felice, Università degli Studi di Camerino, Camerino (Italy) Carlos Gershenson, Universidad Nacional Autónoma de México, Computer Sciences Department, Mexico City (Mexico) Paolo Gibilisco, Università degli Studi di Roma "Tor Vergata", Facoltà di Economia, Roma (Italy) Daniel Polani, University of Hertfordshire, Department of Computer Science, Hatfield (United Kingdom) Mikhail Prokopenko, University of Sydney, Sydney (Australia) Richard Spinney, University of Sydney, Sydney (Australia) Justin Werfel, Harvard University, Cambridge (USA) Larry Yaeger, Google Inc., San Francisco (USA) G. Çiğdem Yalçın, İstanbul Üniversitesi, İstanbul (Turkey)

    Administrative Contact
    Antje Vandenberg
    MPI for Mathematics in the Sciences

Geometric Science of Information

Internal error.

Oops! Looks like something went wrong!