Progress in Information Geometry: Theory and Applications - Brossura

Brossura

ISBN 10: 3030654613 ISBN 13: 9783030654610

Casa editrice: Springer, 2022

Riassunto

This book focuses on information-geometric manifolds of structured data and models and related applied mathematics. It features new and fruitful interactions between several branches of science: Advanced Signal/Image/Video Processing, Complex Data Modeling and Analysis, Statistics on Manifolds, Topology/Machine/Deep Learning and Artificial Intelligence. The selection of applications makes the book a substantial information source, not only for academic scientist but it is also highly relevant for industry. 

The book project was initiated following discussions at the international conference GSI’2019 – Geometric Science of Information that was held at ENAC, Toulouse (France).

Su questo libro

Informazioni sull?autore

<p>Frank Nielsen is Senior Researcher at Sony Computer Science Laboratories Inc, Tokyo, Japan and a fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS).&nbsp;He taught at Ecole Polytechnique (Palaiseau, France) visual computing and high performance computing (HPC) for data science.&nbsp;His research aims at understanding the nature and structure of information and variability in data and exploiting algorithmically this knowledge&nbsp;in innovative imaging and machine learning applications. For that purpose, he coined the field of computational information geometry (computational differential geometry)&nbsp;to extract information as regular structures while taking into account variability in datasets by grounding them in geometric spaces.&nbsp;Geometry beyond Euclidean spaces has a long history of revolutionizing the way we perceived reality.&nbsp;Curved spacetime geometry sustained relativity theory and fractal geometry unveiled the scale-free properties of nature.&nbsp;In the digital world, geometry is data-driven and allows intrinsic data analytics by capturing the very essence of data through invariance principles&nbsp;without being biased by any particular data representation. He is an editor of the journal Entropy (MDPI) and of the journal Information Geometry (INGE, Springer), and co-organize the biannual internation conference on the Geometric Sciences of Information (GSI).</p>

Dalla quarta di copertina

<p>This book focuses on information-geometric manifolds of structured data and models and related applied mathematics. It features new and fruitful interactions between several branches of science: Advanced Signal/Image/Video Processing, Complex Data Modeling and Analysis, Statistics on Manifolds, Topology/Machine/Deep Learning and Artificial Intelligence. The selection of applications makes the book a substantial information source, not only for academic scientist but it is also highly relevant for industry.&nbsp;</p><p>The book project was initiated following discussions at the international conference GSI’2019 – Geometric Science of Information that was held at ENAC, Toulouse (France).<br></p><p><br></p><p></p>

Dettagli dell'edizione

• Editore: Springer
• Data di pubblicazione: 2022
• Lingua: Inglese
• ISBN 10: 3030654613
• ISBN 13: 9783030654610
• Rilegatura: Copertina flessibile
• Numero edizione: 1
• Numero di pagine: 288
• Redattore: Nielsen Frank
• Contatto del produttore: ProductSafety@springernature.com; ProductSafety@springernature.com; ; Poststr. 9; Darmstadt; 64293; Germania