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Group Details

Geometric Science of Information

The objective of this group is to bring together pure/applied mathematicians, physicist and engineers, with common interest for Geometric tools and their applications. It notably aim to organize conferences and to promote collaborative european and international research projects, and diffuse research results on the related domains. It aims to organise conferences, seminar, to promote collaborative local, european and international research project, and to diffuse research results in the the different related interested domains.

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    Job description

    The University of Limerick (UL) with over 15,000 students and 1,400 staff is an energetic and enterprising institution with a proud record of innovation and excellence in education, research and scholarship. The dynamic, entrepreneurial and pioneering values which drive UL’s mission and strategy ensures that we capitalise on local, national and international engagement and connectivity. We are renowned for providing an outstanding student experience and conducting leading edge research. Our commitment is to make a difference by shaping the future through educating and empowering our students. UL is situated on a superb riverside campus of over 130 hectares with the River Shannon as a unifying focal point. Outstanding recreational, cultural and sporting facilities further enhance this exceptional learning and research environment.

    Applications are invited for the following position:

    Faculty of Science + Engineering

    Department of Mathematics & Statistics

    Lecturer and Lecturer below the bar in Statistics & Data Analytics

    Contract Type: Lecturer – Multiannual (Post 1)

    Contract Type: Lecturer below the bar (Post 2) - Tenure Track (five year fixed term).

    During the term of the contract the successful applicant will have the opportunity to apply for tenure in accordance with the University's Policy and Procedures for Granting Multi-annual Status to Tenure Track Academic Staff

    Salary Scale: Lecturer €52,187 - €83,038 p.a.

    Salary Scale: Lecturer below the bar €39,118 - €53,782 p.a.

    Further information for applicants and application material is available online.

    The closing date for receipt of applications is Monday, 3rd December 2018.

    Applications must be completed online before 12 noon, Irish Standard Time on the closing date.

    Please email if you experience any difficulties

    Applications are welcome from suitably qualified candidates.

    The University of Limerick holds a Bronze Athena SWAN award in recognition of our commitment to advancing equality in higher education. The University is an equal opportunities employer and is committed to selection on merit welcoming applicants from all sections of the community. The University has a range of initiatives to support a family friendly working environment, including flexible working.

    “The University of Limerick has implemented a “Smoke and Vape Free Campus Policy”. Smoking and vaping in all forms is prohibited.”

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    The Siri Search team is creating groundbreaking technology for algorithmic search, machine learning, NLP, and artificial intelligence. The features we build are redefining how hundreds of millions of people use their computers and mobile devices to search and find what they are looking for.

    Siri’s universal search engine powers search features across a variety of Apple products, including Siri, Spotlight, Safari, Messages and Lookup. We work with one of the most exciting high performance computing environments, with petabytes of data, millions of queries per second, and have an opportunity to imagine and build products that delight our customers every single day.

    Now imagine what you could do at Apple?

    Key Qualifications
    Industry experience in a Data Science, Machine Learning or Natural Language Processing
    Ability to illuminate complex problems with data analysis
    Proven product success derived from research and analysis results
    Familiarity with Hadoop, Mapreduce and similar technologies
    Experience with machine learning models and systems like Tensorflow
    Programming language like Python or Go
    Experience with Search/Information Retrieval is a plus
    Good communication with internal and external teams
    Fluency in at least one of French, German, Italian, Spanish
    Fluency in English


    This role is part of a growing team so we're you will have the opportunity to work in a few areas including Data Science, ML and NLP. Collaborating with team members in Europe and around the world you can work on many areas including:

    Perform data mining to support new features - Analyze large datasets to glean actionable insights - Design classifiers and ranking algorithms - Perform language processing and query analysis - Perform ad-hoc statistical analysis - Present results of analysis to team and leadership across Apple - Craft metrics to measure the success of the service

    If this is you, we'd love to hear from you.

    Education & Experience

    MS or Ph.D. in Data Mining, Machine Learning, Statistics, Natural Language Processing (in European languages), Operations Research or related field

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    Capture du 2018-11-26 23-17-57.png



    Le GRETSI et le GdR ISIS organisent depuis 2006 une École d'Été annuelle en traitement du signal et des images. Ouverte à toute personne intéressée (académique ou industrielle), elle s'adresse prioritairement à des doctorants ou chercheurs en début de carrière, et a pour but de présenter une synthèse ainsi que les avancées les plus récentes dans un thème de recherche d'actualité. Cette École d'Été a lieu tous les ans et a pour cadre le magnifique village de Peyresq, perché à 1500 mètres d'altitude sur un éperon rocheux des Alpes de Haute Provence (

    Thème de l'école 2019

    La session 2019 a pour thème :

    Géométrie de l'information pour le traitement du signal et des images

    La géométrie de l’information est un thème qui a généré une activité croissante dans la communauté signal et images. Parmi les thématiques incluses dans la géométrie de l’information, on compte par exemple : la définition de distances ou divergences sur des espaces courbes et les applications en classification, les statistiques sur les groupes et les variétés avec des applications en tracking, filtrage et estimation; ainsi que la caractérisation des performances des estimateurs de matrices de covariance. Le nombre des applications est croissant et les potentialités importantes, mais il faut constater que les méthodologies et concepts impliqués en géométrie de l’information ne font pas partie de beaucoup de cursus. Cette École d’Été envisage de proposer aux doctorants (en priorité) une introduction aux concepts de la théorie (géométrie différentielle) ainsi qu’un état des lieux de leurs applications en traitement des signaux et des images.
    L'École comporte à la fois des cours tutoriaux et des sessions ouvertes permettant aux participants de présenter leurs travaux et de confronter leurs idées.
    Vous pouvez télécharger l'affiche et diffuser l'information autour de vous.

    L'École comportera à la fois des cours tutoriaux, ainsi que des sessions ouvertes permettant aux participants de présenter leurs travaux et de confronter leurs idées.
    L'emploi du temps détaillé de l'École sera prochainement disponible.
    Programme prévisionnel

    1. Introduction aux outils de géométrie différentielle et optimisation en traitement des données (5h)
    Conférencier : P.A. Absil (University of Louvain, Belgium)

    2. Géométrie de l’information et ses applications (5h)
    Conférencier : F. Nielsen (Sony Computer Science Laboratories Inc & Ecole Polytechnique)

    3. Statistiques géométriques et leurs applications aux formes anatomiques (5h)
    Conférencier : X. Pennec (INRIA Sophia Antipolis)

    4. Estimation récursive sur les variétés Riemanniennes (2h)
    Conférencier : S. Said (Université de Bordeaux)

    5. Bornes de Cramér-Rao intrinsèques et matrices de covariance (2h)
    Conférencier : A. Renaux (Université Paris Saclay)

    6. Les structures élémentaires de la géométrie de l'information et la métrique de Fisher-Koszul-Souriau : exemples d'applications pour le signal radar (2h)
    Conférencier : F. Barbaresco (Thales)

    Les demandes d'inscriptions à l'École d'Été seront ouvertes à partir de la fin Novembre 2018.
    L'École d'Été est ouverte à toute personne intéressée, académique ou industrielle. Le nombre de participants étant toutefois limité par la capacité d'accueil du lieu, une priorité sera donnée aux doctorants, aux chercheurs en début de carrière et aux industriels partenaires du GdR ISIS.
    Une participation financière couvrant les frais d'hébergement et de restauration est demandée.
    La participation aux frais est de 350€ pour les doctorants et de 600€ pour les autres (chercheurs titulaires, ingénieurs, post-doctorants, industriels).

    Dates importantes

    • novembre 2018: Ouverture du service d'enregistrement des demandes d'inscription.
    • 18 février 2019: Clôture du service d'enregistrement des demandes d'inscription.
    • 19 mars 2019: Notification des inscriptions. Ouverture du service des inscriptions définitives.
    • 3 mai 2019: Fermeture du service des inscriptions définitives.
    • 30 juin - 6 juillet 2019: École d'Eté.

    Comite d'Organisation

    • Patrick Flandrin Directeur de Recherche CNRS, Laboratoire de Physique, ENS de Lyon.
    • Cédric Richard Professeur des Universités, Laboratoire Lagrange, Université de Nice.

    Direction Scientifique

    Pour toute demande de renseignement, veuillez nous envoyer un mèl à
    peyresq19_l AT

    Quand arriver à Peyresq (et en repartir) ?
    Pour des raisons pratiques d'organisation, l'arrivée à Peyresq devra se faire impérativement dans l'après-midi ou le début de soirée du dimanche 30 juin (pas avant pour cause d'occupation du site, et pas après car les cours commenceront le lundi matin à 9h00).
    Comment accéder à Peyresq (et en repartir) ?
    1- Par bus Un bus gratuit sera mis à la disposition des participants pour effectuer directement les trajets entre Nice et Peyresq (2 heures environ). Aller : départ de la gare SNCF de Nice à 17h puis du terminal 2 de l'aéroport de Nice le dimanche 30 juin à 17h30.
    Retour : départ de Peyresq le samedi 6 juillet à 9h00, passage au terminal 2 de l'aéroport de Nice à 11h30 puis en gare SNCF à 12h.
    2- Par le train: Se rendre à la "Gare du Sud (des Chemins de Fer de Provence)", 4 rue Alfred Binet, située à 15 minutes environ de la Gare principale de Nice Prendre le train des Pignes" (qui mène à Digne) et descendre à Annot. Les horaires sont consultables sur le site des Chemins de Fer de Provence. Il est à noter que la liaison entre Annot et Peyresq (20 km) nécessite alors un taxi, qu'il est prudent de réserver (
    3- Par la route : Coordonnées GPS : (N 44° 04' 02" - E 06° 37' 04") Attention : une fois arrivé à Peyresq, il est impératif de se garer à l'extérieur du village.

    Capture du 2018-11-26 23-33-01.png

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    The Numerical Tours of Data Sciences

    The Numerical Tours of Data Sciences, by Gabriel Peyré, gather Matlab, Python, Julia and R experiments to explore modern mathematical data sciences. They cover data sciences in a broad sense, including imaging, machine learning, computer vision and computer graphics. It showcases application of numerical and mathematical methods such as convex optimization, PDEs, optimal transport, inverse problems, sparsity, etc. The tours are complemented by slides of courses detailing the theory and the algorithms.

    Numerical Tours now in R
    Link - 35 R tours available
    Posted by Gabriel Peyré on February 26, 2018

    Numerical Tours on Machine Learning
    Link - 4 new Matlab and Python tours
    Posted by Gabriel Peyré on August 11, 2017

    Numerical Tours now in Julia
    Link - 30 Julia tours available
    Posted by Gabriel Peyré on August 5, 2017

    Numerical Tours now in Python
    Link - 30 Python tours available
    Posted by Gabriel Peyré on September 17, 2016

    New Python Tours
    Optimization by Laurent Condat
    Posted by Gabriel Peyré on June 14, 2016

    Capture du 2018-11-25 13-59-26.png
    Numerical Tours now in R
    The R tours, that can be browsed as HTML pages, but can also be downloaded as Jupyter notebooks. Please read the installation page for more information about how to run these tours.



    Approximation, Coding and Compression


    Inverse Problems


    Machine Learning


    Audio Processing

    Computer Graphics

    Mesh Parameterization and Deformation

    Geodesic Processing

    Optimal Transport

    Capture du 2018-11-25 14-31-08.png


    hese are the Python tours, that can be browsed as HTML pages, but can also be downloaded as Jupyter notebooks. Please read the installation page for more information about how to run these tours.



    Approximation, Coding and Compression


    Inverse Problems



    Audio Processing

    Computer Graphics

    Mesh Parameterization and Deformation

    Geodesic Processing

    Optimal Transport

    Machine Learning

    posted in GSI FORGE read more
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    Postdoctoral position in Computer Vision & Machine Learning - [ Postdoc ] BC 75470
    Workplace: Genova, IIT, Italy
    Added on: 26/06/2018 - Expires on 31/12/2018

    The Pattern Analysis and Computer Vision Research Line (PAVIS) at IIT in Genova is looking for a highly qualified post doc with a strong background in Computer Vision, Pattern Recognition and Machine Learning, with particular emphasis on recognition, video analysis, behavior understanding, and prediction. As the activities may be carried out in collaboration with other IIT research units, the previous multidisciplinary experience is an added value which will be duly considered.
    The main mission of PAVIS is to design and develop innovative image- and video-based intelligent systems, characterized by the use of highly functional smart sensors and advanced data analytics features. PAVIS also plays an active role in supporting the other IIT research units providing scientists in Neuroscience, Nanophysics and other IIT departments/centers with ad-hoc solutions.
    To this end, the group is involved in activities concerning computer vision and pattern recognition, machine learning, multimodal\multimedia data analysis and sensor fusion, and embedded computer vision systems. The lab will pursue this goal by working collaboratively and in cooperation with external private and public partners.

    In particular, this call aims at consolidating PAVIS expertise in the video surveillance area and especially on action/activity recognition and scene understanding from video sequences and other sensory modalities.
    In particular, the following topics are of interest:
    Analysis of static and dynamic scenes.
    Recognition (objects, scenes, actions, events, etc.) and reconstruction.
    Behavior Analysis and Activity Recognition (individuals, groups, crowd).
    Prediction of intentions.
    Domain Adaptation.
    Multimodal data analysis
    Zero-shot Learning

    From the methodological standpoint, the ideal candidate should be familiar with one or more of the following subjects (it’s not an exhaustive list): Deep Learning, Graphical Models, Topic Models, Representation/Feature Learning, Sparse and Dictionary Learning, Clustering, Kernel methods, Manifold Learning and Statistical and Probabilistic Models in general.
    Candidates to this position have a Ph.D. in Computer Vision, Machine Learning, Pattern Recognition or related areas. Research experience and qualification in computer vision and pattern recognition/machine learning are clearly a must and evidence of top quality research on the above-specified areas in the form of published papers in top conferences/journals and/or patents is mandatory.
    Moreover, experience in the preparation and management of research proposals (EU, US, national) and industrial research projects, a few years of postdoc experience, either in academia or in an industrial lab, will also be duly considered. The winning candidate will also be asked to contribute to setting up new (funding) project proposals and will participate in funding activities.
    He/she is also expected to publish his/her research results in leading international journals and conferences, supervise Ph.D. candidates and collaborate with other scientists, also with different expertise.
    Salary will be commensurate to qualification and experience and in line with international standards.
    Further details and informal inquiries can be made by email to quoting PAVIS-PD 75470 as the reference number.
    Please send your completed application forms by December 31, 2018. The application must include: a curriculum listing all publications (possibly including a pdf of your most representative publications), a research statement describing your previous research experience and outlining its relevance to the above topics and the name of 2 referees by email to quoting PAVIS-PD 75470 as the reference number.

    IIT was established in 2003 and successfully created a large-scale infrastructure in Genova, a network of 10-state-of-the-art laboratories countrywide and recruited an international staff of about 1100 people from more than 50 countries. IIT's research endeavor focuses on high-tech and innovation, representing the forefront of technology with possible applications from medicine to industry, computer science, robotics, life sciences, and nanobiotechnologies.
    We inform you that the information you provide will be used solely for the purposes of evaluating and selecting professional profiles in order to meet the requirements of Istituto Italiano di Tecnologia.
    Your data will be processed by Istituto Italiano di Tecnologia, based in Genoa, Via Morego 30, acting as Data Controller, in compliance with the rules on protection of personal data, including those related to data security.
    Please also note that, pursuant to articles 15 et. seq. of European Regulation no. 679/2016 (General Data Protection Regulation), you may exercise your rights at any time by contacting the Data Protection Officer (phone +39 010 71781 - email:
    Istituto Italiano di Tecnologia is an Equal Opportunity Employer that actively seeks diversity in the workforce.

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    Capture du 2018-11-18 21-45-27.png
    ENAC, Toulouse (France)
    7, avenue Edouard BelinCS 54005
    31055 Toulouse Cedex 4
    GPS ccordinates GPS : 43.565156, 1.479281

    Ecole Nationale de l'Aviation Civile
    7, avenue Edouard Belin CS 54005
    31055 Toulouse Cedex 4


    Shuttle from Toulouse-Blagnac Airport

    Free "Airport" shuttle, reserved for ENAC students, teachers and speakers according to availability.
    Boarding on presentation of notification or student / trainee card.

    By public transport

    All information, maps and directions for public transportation in Toulouse are available on Tisseo website ///

    • N°68 - to La terrasse / Métro Ramonville
    • N°78 - to Université Paul Sabatier / Lycée St Orens
    • N°37 - to Jolimont / Métro Ramonville

    Subway - Line B

    • Get off at Faculté de pharmacieFaculty and take bus N°78 to Lycée St Orens
    • Get off at Ramonville-Saint-Agne and take bus N°68 to "La terrasse"

    Subway - Line A

    Get off at Jolimont and take bus N°37 to Ramonville Metro or bus N°68

    By car
    Take outer ring road (towards "Montpellier"), then follow "Toulouse center / Foix / Tarbes" (green sign). Exit N°20, follow "Complexe scientifique Rangueil".
    GPS : 43.565156, 1.479281


    Capture du 2018-11-18 21-57-34.png

    Social events
    Welcome Coktail
    will take place 27th August at "Mairie de Toulouse Palace” gsi2019-se1.jpg

    Gala Diner
    will take place 28th August at Hôtel-Dieu Saint-Jacques in Salle Des Colonnes. »
    gsi2019-se3.jpg gsi2019-se2.jpg gsi2019-se4.jpg

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    Conference Co-chairs:

    Frank Nielsen- Sony CSL, Japan, Ecole Polytechnique, France Frank.png
    Frédéric Barbaresco - President of SEE ISIC Club Ingénierie des Systèmes d’Information et de Communications, Thales Land & Air Systems, Limours, France Frédéric.png

    Local organizing committee:

    Scientific Committee (To be consolidated)

    • Bijan Afsari – Johns Hopkins University
    • Pierre-Antoine Absil – Université Catholique de Louvain
    • Stephanie Allasonnière – Paris-Diderot University
    • Jesus Angulo – Mines ParisTech
    • Marc Arnaudon – Bordeaux University
    • John Armstrong – King’s College London
    • Anne Auger – Ecole Polytechnique
    • Nihat Ay – Max Planck Institute
    • Roger Balian – CEA
    • Frédéric Barbaresco – Thales Land & Air Systems
    • Pierre Baudot – MEDIAN
    • Daniel Bennequin – Paris-Diderot University
    • Joel Bensoam – IRCAM
    • Yannick Berthoumieu – Bordeaux University
    • Jeremie Bigot – Bordeaux University
    • Silvere Bonnabel – Mines ParisTech
    • Michel Broniatowski – Sorbonne University
    • Michel Boyom – Montpellier University
    • Marius Buliga – Simion Stoilow Institute of Mathematics of the Romanian Academy
    • Laurent Cohen – Paris Dauphine University
    • Ana Bela Cruzeiro – Universidade de Lisboa
    • Remco Duits - Eindhoven University of Technology
    • Stanley Durrleman – INRIA
    • Alfred Galichon – New York University
    • Fabrice Gamboa – Institut Mathématique de Toulouse
    • Jean-Pierre Gazeau – Paris Diderot University
    • François Gay-Balmaz – ENS Ulm
    • Mark Girolami – Imperial College London
    • Susan Holmes – Stanford University
    • Jérémie J. Jakubowicz – Telecom SudParis
    • Jean Lerbet – Evry University
    • Nicolas Le Bihan – Grenoble University
    • Luigi Malago – Romanian Institute of Science and Technology
    • Jonathan Manton - The University of Melbourne
    • Gaetan Marceau-Caron – MILA R&D and Tech Transfer
    • Matilde Marcolli - CALTECH
    • Jean-François Marcotorchino – Sorbonne University
    • Charles-Michel Marle – Sorbonne University
    • Hiroshi Matsuzoe - Nagoya Institute of Technology
    • Jean-Marie Mirebeau – Paris Orsay University
    • Ali Mohammad-Djafari – Centrale Supelec
    • Antonio Mucherino - IRISA, University of Rennes 1
    • Florence Nicol - ENAC
    • Frank Nielsen - Ecole Polytechnique, Paris-Saclay University
    • Richard Nock - Université Antilles-Guyane
    • Yann Ollivier – FACEBOOK FAIR Paris
    • Steve Oudot – INRIA
    • Pierre Pansu – Paris-Saclay University
    • Xavier Pennec - INRIA
    • Giovanni Pistone – CarloAlberto University
    • Stephane Puechmorel - ENAC
    • Olivier Rioul – Telecom ParisTech
    • Gery de Saxcé – Lille University
    • Salem Said – Bordeaux University
    • Rodolphe Sepulchre – Liège University
    • Olivier Schwander – Sorbonne University
    • Stefan Sommer – Copenhagen University
    • Dominique Spehner – Grenoble University
    • Alain Trouvé – Ecole Normale Supérieure Paris-Saclay
    • Geert Verdoolaege – Ghent University
    • Rene Vidal – Johns Hopkins University
    • Jun Zhang – University of Michigan, Ann Arbor

    Please use the form below to contact them electronically.

    • ALIDOR Valérie
      SEE – Congress
      Société de l'Electricité, de l'Electronique
      et des Technologies de l'Information
      et de la Communication
      17 rue de l'Amiral Hamelin
      75783 Paris Cedex16
      Phone: +33 (0)1 56 90 37 02
    • Frank NIELSEN
      Professor (PhD 1996, Habilitation 2006)
      Campus de l'École Polytechnique
      1, rue Honoré d'Estienne d'Orves
      Bâtiment Alan Turing
      91120 Palaiseau
      Phone: +33 (0)1 77 57 80 70
      (Office 2028)

    • Frédéric BARBARESCO
      Technical Directorate
      Advanced Department Developments
      Voie Pierre-Gilles de Gennes, F-91470 Limours, FRANCE
      Phone: +33 (0)6 30 07 14 19

    Capture du 2018-11-18 21-57-34.png

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    Capture du 2018-11-18 21-45-27.png
    PROBABILITY & GEOMETRY OF CHANCE (invention by Pierre de FERMAT and Blaise PASCAL in letters of their correspondence)
    Seminal Blaise Pascal paper – ALEAE GEOMETRIA, De compositione aleae in ludis ipsi subjectis, Celeberrimae matheseos Academiae Parisiensi – 1654. « ... inviter les savants géomètres à traiter nos problèmes avec le soucis de la commodité et de l’agrément : qu’ils écartent tout ce qui n’a rien à voir avec la pénétration de l’esprit, seule qualité dont nous faisons grand cas et que nous nous sommes proposé d’éprouver et de couronner » Blaise Pascal – Deuxième Lettre sur la roulette, Paris, 19 Juillet 1658


    Submission dates

    • Deadline for 8 pages SPRINGER LNCS format: 18th of February 2019
    • Notification of acceptance: 22nd of April 2019
    • Final paper submission: 15th of June 2019

    Submission page :

    GSI2019 Call for Papers
    GSI2019 Word splnproc1703
    GSI2019 Latex-llncs2e template
    GSI2019 Copyright Form Springer

    Capture du 2018-11-18 21-57-34.png

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    Capture du 2018-11-18 21-45-27.png


    4th conference on Geometric Science of Information - 27 August 2019 - 29 August 2019 ENAC, Toulouse (France)

    As for GSI’13, GSI’15 and GSI’17, the objective of this SEE GSI’19 conference, hosted in Toulouse at ENAC, 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, Learning for Robotics, etc., which are substantially relevant for industry.
    The Conference will be therefore held in areas of 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

    This conference will be an interdisciplinary event and will unify skills from Geometry, Probability and Information Theory. Proceedings are published in Springer's Lecture Note in Computer Science (LNCS) series. SPRINGER will sponsor Best paper Award GSI’19.
    Gala Diner will take place at Hôtel-Dieu Saint-Jacques in Salle Des Colonnes.

    Provisional topics of interests:

    • Probability on Riemannian Manifolds
    • Optimization on Manifold
    • Shape Space
    • Statistics on non-linear data
    • Lie Group Machine Learning
    • Harmonic Analysis on Lie Groups
    • Statistical Manifold & Hessian Information Geometry
    • Monotone Embedding in Information Geometry
    • Non-parametric Information Geometry
    • Computational Information Geometry
    • Divergence Geometry
    • Optimal Transport
    • Geometric Deep Learning
    • Geometry of Hamiltonian Monte Carlo
    • Information Topology
    • Geometric & (Poly)Symplectic Integrators
    • Geometric structures in thermodynamics and statistical physics
    • Contact Geometry & Hamiltonian Control
    • Geometric and structure preserving discretizations
    • Geometry of Quantum States
    • Geodesic Methods with Constraints
    • Probability Density Estimation & Sampling in High Dimension
    • Geometry of Graphs and Networks
    • Distance Geometry
    • Geometry of Tensor-Valued Data
    • Geometric Mechanics
    • Geometric Robotics & Learning
    • Geometry in Neuroscience & Cognitive Sciences

    A special session will deal with:

    • Geometric Science of Information Libraries (geomstats, pyRiemann , …)

    Important dates

    • Deadline for 8 pages SPRINGER LNCS format: 18th of February 2019
    • Notification of acceptance: 22nd of April 2019
    • Final paper submission: 15th of June 2019

    Provisional program of Invited Speakers:
    History Session: TBC on “Fermat, Pascal & the Geometry of Chance”, Frédéric Barbaresco & Michel Boyom “Tribute to Jean-Louis Koszul (who passed away in January 2018)”
    Invited Honorary speaker: TBC, Guest Honorary speaker: TBC, and 3 keynotes Speakers: TBC
    (TBC: To be Confirmed)

    Capture du 2018-11-18 21-57-34.png

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    Samedi 17 novembre 2018
    Amphi Hermite, Institut Henri Poincaré

    • Kirone Mallick - Thermodynamique et information • 10h
    • Olivier Rioul - La théorie de l’information sans peine • 11h
    • Sergio Ciliberto - Landauer et le démon de Maxwell • 14h
    • Elham Kashefi - Quantum Verification • 15h
    • Christophe Salomon - La simulation quantique • 16h

    posted in Bourbaphy Seminar - INFORMATION read more
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