Geometric Science of Information

Geometric Science of Information : Third International Conference, GSI 2017, Paris, France, November 7-9, 2017, Proceedings

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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.
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Product details

  • Paperback | 877 pages
  • 155 x 235 x 45.47mm | 1,238.31g
  • Cham, Switzerland
  • English
  • 1st ed. 2017
  • 168 Illustrations, black and white; XXV, 877 p. 168 illus.
  • 3319684442
  • 9783319684444

Table of contents

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.
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