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Machine learning as a tool in theoretical science

Nature Reviews Physics volume 4, pages 145–146 (2022)Cite this article

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Machine learning methods relying on synthetic data are starting to be used in mathematics and theoretical physics. Michael R. Douglas discusses recent advances and ponders on the impact these methods will have in science.

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Authors and Affiliations

  1. Harvard University, Cambridge, MA, USA

    Michael R. Douglas

  2. Stony Brook University, Stony Brook, NY, USA

    Michael R. Douglas

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  1. Michael R. Douglas
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Correspondence to Michael R. Douglas.

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The author declares no competing interests.

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Douglas, M.R. Machine learning as a tool in theoretical science. Nat Rev Phys 4, 145–146 (2022). https://doi.org/10.1038/s42254-022-00431-9

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