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(Ebook) Geometric Science of Information: 5th International Conference, GSI 2021, Paris, France, July 21–23, 2021, Proceedings (Lecture Notes in Computer Science, 12829) by Frank Nielsen (editor), Frédéric Barbaresco (editor) ISBN 9783030802080, 3030802086

  • SKU: EBN-51579278
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Instant download (eBook) Geometric Science of Information: 5th International Conference, GSI 2021, Paris, France, July 21–23, 2021, Proceedings (Lecture Notes in Computer Science, 12829) after payment.
Authors:Frank Nielsen (editor), Frédéric Barbaresco (editor)
Pages:958 pages.
Year:2021
Editon:1st ed. 2021
Publisher:Springer
Language:english
File Size:15.8 MB
Format:pdf
ISBNS:9783030802080, 3030802086
Categories: Ebooks

Product desciption

(Ebook) Geometric Science of Information: 5th International Conference, GSI 2021, Paris, France, July 21–23, 2021, Proceedings (Lecture Notes in Computer Science, 12829) by Frank Nielsen (editor), Frédéric Barbaresco (editor) ISBN 9783030802080, 3030802086

This book constitutes the proceedings of the 5th International Conference on Geometric Science of Information, GSI 2021, held in Paris, France, in July 2021.The 98 papers presented in this volume were carefully reviewed and selected from 125 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. The papers are organized in the following topics: Probability and statistics on Riemannian Manifolds; sub-Riemannian geometry and neuromathematics; shapes spaces; geometry of quantum states; geometric and structure preserving discretizations; information geometry in physics; Lie group machine learning; geometric and symplectic methods for hydrodynamical models; harmonic analysis on Lie groups; statistical manifold and Hessian information geometry; geometric mechanics; deformed entropy, cross-entropy, and relative entropy; transformation information geometry; statistics, information and topology; geometric deep learning; topological and geometrical structures in neurosciences; computational information geometry; manifold and optimization; divergence statistics; optimal transport and learning; and geometric structures in thermodynamics and statistical physics.
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