Uncertainty quantification for misspecified machine learned interatomic potentials

Abstract The use of high-dimensional regression techniques from machine learning has significantly improved the quantitative accuracy of interatomic potentials. Atomic simulations can now plausibly target quantitative predictions in a variety of settings, which has brought renewed interest in robust...

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Bibliographic Details
Main Authors: Danny Perez, Aparna P. A. Subramanyam, Ivan Maliyov, Thomas D. Swinburne
Format: Article
Language:English
Published: Nature Portfolio 2025-08-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-025-01758-4
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