Retrospective on a decade of machine learning for chemical discovery

O. Anatole von Lilienfeld () and Kieron Burke ()
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O. Anatole von Lilienfeld: University of Vienna
Kieron Burke: University of California, Irvine

Nature Communications, 2020, vol. 11, issue 1, 1-4

Abstract: Standfirst Over the last decade, we have witnessed the emergence of ever more machine learning applications in all aspects of the chemical sciences. Here, we highlight specific achievements of machine learning models in the field of computational chemistry by considering selected studies of electronic structure, interatomic potentials, and chemical compound space in chronological order.

Date: 2020
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DOI: 10.1038/s41467-020-18556-9

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