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This Special Issue of the journal Entropy, titled “Information Geometry I”, contains a collection of 17 papers concerning the foundations and applications of information geometry. Based on a geometrical interpretation of probability, information geometry has become a rich mathematical field employing the methods of differential geometry.
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Connecting Information Geometry and Geometric Mechanics
The divergence function in information geometry, and the discrete Lagrangian in discrete geometric mechanics each induce a differential geometric structure on the product manifold Q × Q .
Melvin Leok, Jun Zhang
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Kählerian Information Geometry for Signal Processing
We prove the correspondence between the information geometry of a signal filter and a Kähler manifold. The information geometry of a minimum-phase linear system with a finite complex cepstrum norm is a Kähler manifold.
Jaehyung Choi, Andrew P. Mullhaupt
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The asymmetric skew divergence smooths one of the distributions by mixing it, to a degree determined by the parameter λ, with the other distribution. Such divergence is an approximation of the KL divergence that does not require the target distribution ...
Masanari Kimura, Hideitsu Hino
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A Simple Approximation Method for the Fisher–Rao Distance between Multivariate Normal Distributions
We present a simple method to approximate the Fisher–Rao distance between multivariate normal distributions based on discretizing curves joining normal distributions and approximating the Fisher–Rao distances between successive nearby normal ...
Frank Nielsen
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Categorical Information Geometry
Information geometry is the study of interactions between random variables by means of metric, divergences, and their geometry. Categorical probability has a similar aim, but uses algebraic structures, primarily monoidal categories, for that purpose.
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Geometric Structures Induced by Deformations of the Legendre Transform
The recent link discovered between generalized Legendre transforms and non-dually flat statistical manifolds suggests a fundamental reason behind the ubiquity of Rényi’s divergence and entropy in a wide range of physical phenomena.
Pablo A. Morales +2 more
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Far from Asymptopia: Unbiased High-Dimensional Inference Cannot Assume Unlimited Data
Inference from limited data requires a notion of measure on parameter space, which is most explicit in the Bayesian framework as a prior distribution. Jeffreys prior is the best-known uninformative choice, the invariant volume element from information ...
Michael C. Abbott, Benjamin B. Machta
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Entropic Dynamics in a Theoretical Framework for Biosystems
Central to an understanding of the physical nature of biosystems is an apprehension of their ability to control entropy dynamics in their environment.
Richard L. Summers
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F‐Manifolds and geometry of information [PDF]
The theory of $F$-manifolds, and more generally, manifolds endowed with commutative and associative multiplication of their tangent fields, was discovered and formalised in various models of quantum field theory involving algebraic and analytic geometry, at least since 1990's. The focus of this paper consists in the demonstration that various spaces of
Combe , N., Manin, Y.
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