CT GSI Geometric Sciences of Information
Prochaines manifestations

Accueil
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.
It emphasizes an active participation of engineers and researchers to develop emerging areas of collaborative research on “Information Geometry and Their Advanced Applications”. Current and ongoing uses of Information Geometry in applied mathematics are the following:
 Thermodynamic, statistical physic.
 Advanced Signal/Image/Video Processing, medical imaging
 Complex Data Modeling and Analysis, Topological data analysis, dimension reduction, clustering, pattern detection
 Information Ranking and Retrieval, Coding, Compression
 Cognitive Systems, Artificial intelligence, Neural networks, Optimal Control, biological modelisation and computational morphology, Speechsound recognition, natural language treatment.
 Quantum information, correlations, coding
 Statistics on Manifolds, Machine Learning, Manifold Learning
 etc...
which are also substantially relevant for industry and current social challenges.
Informations
the fundamental theorem of information geometry, and illustrate some uses of these information
manifolds in information sciences. The exposition is selfcontained by concisely introducing the
necessary concepts of diﬀerential geometry with proofs omitted for brevity.
[32] TODHUNTER, I., A History of Mathematical Theory of Probability from the Time of Pascal to that of Laplace, Cambridge et Londres, Macmillan, 1865.
Organization
Président
Frédéric Barbaresco 
Bureau
Pierre Baudot  Frank Nielsen 
Links
Sub groups/sites
Events
2019

2018
2017


2015

2014

2013

Documents
Opening and closing sessions (chaired by Frédéric Barbaresco, Frank Nielsen, Silvère Bonnabel)
the fundamental theorem of information geometry, and illustrate some uses of these information
manifolds in information sciences. The exposition is selfcontained by concisely introducing the
necessary concepts of diﬀerential geometry with proofs omitted for brevity.
Bibliography
This Special Issue "Differential Geometrical Theor y of Statistics" collates selected invited and contributed talks presented during the conference GSI'15 on "Geometric Science of Information" which was held at the Ecole Polytechnique, ParisSaclay Campus, France, in October 2015 (Conference web site: http://www.see.asso.fr/gsi2015).
www.mdpi.com/journal/entropy/special_issues/entropystatistics
ISBN 9783038424246 (print) • ISBN 9783038424253 (electronic) 

Author: Frédéric Barbaresco, Ali MohammadDjafari
Publisher: MDPI (2015), Binding: Paperback, 542 pages


EditorinChief: Shinto Eguchi
CoEditors: N. Ay; F. Nielsen; J. Zhang


This book focuses on information geometry manifolds of structured data/information and their advanced applications featuring new and fruitful interactions between several branches of science: information science, mathematics and physics. It addresses interrelations between different mathematical domains like shape spaces, probability/optimization & algorithms on manifolds, relational and discrete metric spaces, computational and Hessian information geometry, algebraic/infinite dimensional/Banach information manifolds, divergence geometry, tensorvalued morphology, optimal transport theory, manifold & topology learning, and applications like geometries of audioprocessing, inverse problems and signal processing. The book collects the most important contributions to the conference GSI’2017 – Geometric Science of Information. 

News
Topics of interests will include, but not be limited to, the Fisher–Rao metric, dual connections, divergence functions, entropy/crossentropy, Hessian geometry, exponential/mixture geodesics and projections, Qstatistics, 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.