Geometric Structures of Information

Β· Springer
ЭлСктронная ΠΊΠ½ΠΈΠ³Π°
392
ΠšΠΎΠ»ΠΈΡ‡Π΅ΡΡ‚Π²ΠΎ страниц

Об элСктронной ΠΊΠ½ΠΈΠ³Π΅

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 ...

Π”Ρ€ΡƒΠ³ΠΈΠ΅ прСдлоТСния

Об Π°Π²Ρ‚ΠΎΡ€Π΅

Frank Nielsen is Professor at the Laboratoire d'informatique de l'Γ‰cole polytechnique, Paris, France. His research aims at understanding the nature and structure of information and randomness in data, and exploiting algorithmically this knowledge in innovative imaging applications. For that purpose, he coined the field of computational information geometry (computational differential geometry) to extract information as regular structures whilst taking into account variability in datasets by grounding them in geometric spaces. Geometry beyond Euclidean spaces has a long history of revolutionizing the way we perceived reality. Curved spacetime geometry, sustained relativity theory and fractal geometry unveiled the scale-free properties of Nature. In the digital world, geometry is data-driven and allows intrinsic data analytics by capturing the very essence of data through invariance principles without being biased by such or such particular data representation.

Frank Nielsen is Professor at the Laboratoire d'informatique de l'Γ‰cole polytechnique, Paris, France. His research aims at understanding the nature and structure of information and randomness in data, and exploiting algorithmically this knowledge in innovative imaging applications. For that purpo...

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