Spectral operator representations

Abstract Machine learning in atomistic materials science has grown to become a powerful tool, with most approaches focusing on atomic geometry, typically decomposed into local atomic environments. This approach, while well-suited for machine-learned interatomic potentials, is conceptually at odds wi...

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Bibliographic Details
Main Authors: Austin Zadoks, Antimo Marrazzo, Nicola Marzari
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:npj Computational Materials
Online Access:https://doi.org/10.1038/s41524-024-01446-9
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