Nielsen / Barbaresco Geometric Science of Information

Third International Conference, GSI 2017, Paris, France, November 7-9, 2017, Proceedings
1. Auflage 2017
ISBN: 978-3-319-68445-1
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 10589, 877 Seiten, eBook

Reihe: Lecture Notes in Computer Science

This book constitutes the refereed proceedings of the Third International Conference on Geometric Science of Information, GSI 2017, held in Paris, France, in November 2017. The 101 full papers presented were carefully reviewed and selected from 113 submissions and are organized into the following subjects: statistics on non-linear data; shape space; optimal transport and applications: image processing; optimal transport and applications: signal processing; statistical manifold and hessian information geometry; monotone embedding in information geometry; information structure in neuroscience; geometric robotics and tracking; geometric mechanics and robotics; stochastic geometric mechanics and Lie group thermodynamics; probability on Riemannian manifolds; divergence geometry; non-parametric information geometry; optimization on manifold; computational information geometry; probability density estimation; session geometry of tensor-valued data; geodesic methods with constraints; applications of distance geometry.

Zielgruppe

Research

Autoren/Hrsg.

Nielsen, Frank

Barbaresco, Frédéric

Inhaltsverzeichnis

Statistics on non-linear data.- Shape space.- Optimal Transport & Applications.- Statistical Manifold & Hessian Information Geometry.- Statistical Manifold  and Hessian Information Geometry.- Monotone Embedding in Information Geometry.- Information Structure in Neuroscience.- Geometric Robotics and Tracking.- Geometric Mechanics and Robotics.- Stochastic Geometric Mechanics and Lie Group Thermodynamics.- Probability on Riemannian Manifolds.- Divergence Geometry.- Non-parametric Information Geometry.- Optimization on Manifold.- Computational Information Geometry.- Probability Density Estimation.- Session Geometry of Tensor-Valued Data.- Geodesic Methods with Constraints.- Applications of Distance Geometry.