Evaluation of the MACE Force Field Architecture: from Medicinal Chemistry to Materials Science

The MACE architecture represents the state of the art in the field of machine learning force fields for a variety of in-domain, extrapolation and low-data regime tasks. In this paper, we further evaluate MACE by fitting models for published benchmark datasets. We show that MACE generally outperforms...

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Veröffentlicht in:	arXiv.org 2023-07
Hauptverfasser:	Kovacs, David Peter, Ilyes Batatia, Arany, Eszter Sara, Csanyi, Gabor
Format:	Artikel
Sprache:	eng
Schlagworte:	Domains Machine learning Materials science Molecular dynamics Optimization Organic chemistry Physics - Chemical Physics Statistics - Machine Learning Vibrational spectra Water
Online-Zugang:	Volltext
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