LTAU-FF: Loss Trajectory Analysis for Uncertainty in atomistic Force Fields
Model ensembles are effective tools for estimating prediction uncertainty in deep learning atomistic force fields. However, their widespread adoption is hindered by high computational costs and overconfident error estimates. In this work, we address these challenges by leveraging distributions of pe...
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| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
IOP Publishing
2025-01-01
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| coleção: | Machine Learning: Science and Technology |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1088/2632-2153/adb4b9 |
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