Information Geometry
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Beschreibung
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. It has numerous applications to data science, physics, and neuroscience. Presenting original research, yet written in an accessible, tutorial style, this collection of papers will be useful for scientists who are new to the field, while providing an excellent reference for the more experienced researcher. Several papers are written by authorities in the field, and topics cover the foundations of information geometry, as well as applications to statistics, Bayesian inference, machine learning, complex systems, physics, and neuroscience.
Autor*in
Geert Verdoolaege
Themen in »Information Geometry«
Markov random fields information theory Fisher information entropy maximum pseudo-likelihood estimation Bezout matrix Sylvester matrix tensor Sylvester matrix Stein equation Vandermonde matrix stationary process matrix resultant Fisher information matrix information geometry dually flat structure