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