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 |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2021
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Materias: | |
Acceso en línea: | https://doaj.org/article/d464131237b648b2a94206b7d3ce44f4 |
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