Geometric Structures of Information
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Beschreibung
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, tensor-valued morphology, optimal transport theory, manifold & topology learning, and applications like geometries of audio-processing, inverse problems and signal processing.The book collects the most important contributions to the conference GSI’2017 – Geometric Science of Information.
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, tensor-valued morphology, optimal transport theory, manifold & topology learning, and applications like geometries of audio-processing, inverse problems and signal processing.
The book collects the most important contributions to the conference GSI’2017 – Geometric Science of Information.
Features new and fruitful interactions between several branches of science: information science, mathematics and physics Addresses interrelations between different mathematical domains like shape spaces, probability/optimization & algorithms on manifolds Collects the most important contributions to the conference GSI’2017 – Geometric Science of Information
Autor*in
Frank Nielsen
Themen in »Geometric Structures of Information«
Hessian Information Geometry Shape Space Monotone Embedding Stochastic Geometric Mechanics Riemannian Manifolds Geometric Deep Learning Lie Group Thermodynamics Probability Density Estimation Geometry of quantum states GSI’2017