Probabilistic Inference for Dynamical Systems

A general framework for inference in dynamical systems is described, based on the language of Bayesian probability theory and making use of the maximum entropy principle. Taking the concept of a path as fundamental, the continuity equation and Cauchy’s equation for fluid dynamics arise naturally, wh...

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Detalles Bibliográficos
Autores principales: Davis, Sergio, González, Diego, Gutiérrez, Gonzalo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513225/
https://www.ncbi.nlm.nih.gov/pubmed/33265785
http://dx.doi.org/10.3390/e20090696
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author Davis, Sergio
González, Diego
Gutiérrez, Gonzalo
author_facet Davis, Sergio
González, Diego
Gutiérrez, Gonzalo
author_sort Davis, Sergio
collection PubMed
description A general framework for inference in dynamical systems is described, based on the language of Bayesian probability theory and making use of the maximum entropy principle. Taking the concept of a path as fundamental, the continuity equation and Cauchy’s equation for fluid dynamics arise naturally, while the specific information about the system can be included using the maximum caliber (or maximum path entropy) principle.
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spelling pubmed-75132252020-11-09 Probabilistic Inference for Dynamical Systems Davis, Sergio González, Diego Gutiérrez, Gonzalo Entropy (Basel) Article A general framework for inference in dynamical systems is described, based on the language of Bayesian probability theory and making use of the maximum entropy principle. Taking the concept of a path as fundamental, the continuity equation and Cauchy’s equation for fluid dynamics arise naturally, while the specific information about the system can be included using the maximum caliber (or maximum path entropy) principle. MDPI 2018-09-12 /pmc/articles/PMC7513225/ /pubmed/33265785 http://dx.doi.org/10.3390/e20090696 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Davis, Sergio
González, Diego
Gutiérrez, Gonzalo
Probabilistic Inference for Dynamical Systems
title Probabilistic Inference for Dynamical Systems
title_full Probabilistic Inference for Dynamical Systems
title_fullStr Probabilistic Inference for Dynamical Systems
title_full_unstemmed Probabilistic Inference for Dynamical Systems
title_short Probabilistic Inference for Dynamical Systems
title_sort probabilistic inference for dynamical systems
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7513225/
https://www.ncbi.nlm.nih.gov/pubmed/33265785
http://dx.doi.org/10.3390/e20090696
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AT gonzalezdiego probabilisticinferencefordynamicalsystems
AT gutierrezgonzalo probabilisticinferencefordynamicalsystems

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