Learning dominant physical processes with data-driven balance models

The dynamics of complex physical systems can be determined by the balance of a few dominant processes. Callaham et al. propose a machine learning approach for the identification of dominant regimes from experimental or numerical data with examples from turbulence, optics, neuroscience, and combustio...

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Autores principales:	Jared L. Callaham, James V. Koch, Bingni W. Brunton, J. Nathan Kutz, Steven L. Brunton
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/d464131237b648b2a94206b7d3ce44f4
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spelling	oai:doaj.org-article:d464131237b648b2a94206b7d3ce44f42021-12-02T14:03:50ZLearning dominant physical processes with data-driven balance models10.1038/s41467-021-21331-z2041-1723https://doaj.org/article/d464131237b648b2a94206b7d3ce44f42021-02-01T00:00:00Zhttps://doi.org/10.1038/s41467-021-21331-zhttps://doaj.org/toc/2041-1723The dynamics of complex physical systems can be determined by the balance of a few dominant processes. Callaham et al. propose a machine learning approach for the identification of dominant regimes from experimental or numerical data with examples from turbulence, optics, neuroscience, and combustion.Jared L. CallahamJames V. KochBingni W. BruntonJ. Nathan KutzSteven L. BruntonNature PortfolioarticleScienceQENNature Communications, Vol 12, Iss 1, Pp 1-10 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Jared L. Callaham James V. Koch Bingni W. Brunton J. Nathan Kutz Steven L. Brunton Learning dominant physical processes with data-driven balance models
description	The dynamics of complex physical systems can be determined by the balance of a few dominant processes. Callaham et al. propose a machine learning approach for the identification of dominant regimes from experimental or numerical data with examples from turbulence, optics, neuroscience, and combustion.
format	article
author	Jared L. Callaham James V. Koch Bingni W. Brunton J. Nathan Kutz Steven L. Brunton
author_facet	Jared L. Callaham James V. Koch Bingni W. Brunton J. Nathan Kutz Steven L. Brunton
author_sort	Jared L. Callaham
title	Learning dominant physical processes with data-driven balance models
title_short	Learning dominant physical processes with data-driven balance models
title_full	Learning dominant physical processes with data-driven balance models
title_fullStr	Learning dominant physical processes with data-driven balance models
title_full_unstemmed	Learning dominant physical processes with data-driven balance models
title_sort	learning dominant physical processes with data-driven balance models
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/d464131237b648b2a94206b7d3ce44f4
work_keys_str_mv	AT jaredlcallaham learningdominantphysicalprocesseswithdatadrivenbalancemodels AT jamesvkoch learningdominantphysicalprocesseswithdatadrivenbalancemodels AT bingniwbrunton learningdominantphysicalprocesseswithdatadrivenbalancemodels AT jnathankutz learningdominantphysicalprocesseswithdatadrivenbalancemodels AT stevenlbrunton learningdominantphysicalprocesseswithdatadrivenbalancemodels
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Learning dominant physical processes with data-driven balance models

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