Nature Communications (Feb 2021)

Learning dominant physical processes with data-driven balance models

  • Jared L. Callaham,
  • James V. Koch,
  • Bingni W. Brunton,
  • J. Nathan Kutz,
  • Steven L. Brunton

DOI
https://doi.org/10.1038/s41467-021-21331-z
Journal volume & issue
Vol. 12, no. 1
pp. 1 – 10

Abstract

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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.