Special issue on machine learning and data-driven methods in fluid dynamics

Steven L. Brunton, Maziar S. Hemati, Kunihiko Taira

Research output: Contribution to journalEditorialpeer-review

5 Scopus citations
Original languageEnglish (US)
Pages (from-to)333-337
Number of pages5
JournalTheoretical and Computational Fluid Dynamics
Volume34
Issue number4
DOIs
StatePublished - Aug 1 2020

Bibliographical note

Funding Information:
We thank Tim Colonius, Kozo Fujii, Koji Fukagata, Petros Koumoutsakos, Nathan Kutz, Jean-Christophe Loiseau, Bernd Noack, and Peter Schmid for stimulating discussions on data-driven methods and their applications to fluid dynamics.

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