Results 11 to 20 of about 1,328,298 (163)
Geometry from Information Geometry [PDF]
AIP Conference Proceedings, 2015 We use the method of maximum entropy to model physical space as a curved statistical manifold. It is then natural to use information geometry to explain the geometry of space.
Caticha, Ariel
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Nonparametric Information Geometry [PDF]
, 2013 The differential-geometric structure of the set of positive densities on a given measure space has raised the interest of many mathematicians after the discovery by C.R. Rao of the geometric meaning of the Fisher information.
A. Ambrosetti +43 more
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An Elementary Introduction to Information Geometry [PDF]
Entropy, 2020 In this survey, we describe the fundamental differential-geometric structures of information manifolds, state the fundamental theorem of information geometry, and illustrate some use cases of these information manifolds in information sciences.
Frank Nielsen
doaj +4 more sources
Information Geometry on the \(\kappa\)-Thermostatistics [PDF]
Entropy, 2015 We explore the information geometric structure of the statistical manifold generated by the \(\kappa\)-deformed exponential family. The dually-flat manifold is obtained as a dualistic Hessian structure by introducing suitable generalization of the Fisher
Tatsuaki Wada, Antonio M. Scarfone
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Information Geometry and Phase Transitions [PDF]
Physica A: Statistical Mechanics and its Applications, 2004 The introduction of a metric onto the space of parameters in models in Statistical Mechanics and beyond gives an alternative perspective on their phase structure. In such a geometrization, the scalar curvature, R, plays a central role.
D.A. Johnston +11 more
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Divergence functions in Information Geometry [PDF]
, 2019 A recently introduced canonical divergence $\mathcal{D}$ for a dual structure $(\mathrm{g},\nabla,\nabla^*)$ is discussed in connection to other divergence functions.
J Zhang +9 more
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Pullback Bundles and the Geometry of Learning
Entropy, 2023 Explainable Artificial Intelligence (XAI) and acceptable artificial intelligence are active topics of research in machine learning. For critical applications, being able to prove or at least to ensure with a high probability the correctness of algorithms
Stéphane Puechmorel
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Statistical Analysis of Plasma Dynamics in Gyrokinetic Simulations of Stellarator Turbulence
Entropy, 2023 A geometrical method for assessing stochastic processes in plasma turbulence is investigated in this study. The thermodynamic length methodology allows using a Riemannian metric on the phase space; thus, distances between thermodynamic states can be ...
Aristeides D. Papadopoulos +4 more
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Quantum information geometry of driven CFTs
Journal of High Energy Physics, 2023 Driven quantum systems exhibit a large variety of interesting and sometimes exotic phenomena. Of particular interest are driven conformal field theories (CFTs) which describe quantum many-body systems at criticality.
Jan de Boer +3 more
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How Morphological Computation Shapes Integrated Information in Embodied Agents
Frontiers in Psychology, 2021 The Integrated Information Theory provides a quantitative approach to consciousness and can be applied to neural networks. An embodied agent controlled by such a network influences and is being influenced by its environment.
Carlotta Langer +5 more
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