EGraFFBench: Analysis of Equivariant Graph Neural Community Power Fields for Atomistic Simulations

Digital Discovery, 2024, Accepted Manuscript
DOI: 10.1039/D4DD00027G, Paper

Open Access

&nbsp This article is licensed under a Creative Commons Attribution 3.0 Unported Licence.

Vaibhav Bihani, Sajid Mannan, Utkarsh Pratiush, Tao Du, Zhimin Chen, Santiago Miret, Matthieu Micoulaut, Morten M Smedskjaer, Sayan Ranu, N. M. Anoop Krishnan
Equivariant graph neural networks force fields (EGRAFFs) have shown great promise in modelling complex interactions in atomic systems by exploiting the graphs’ inherent symmetries. Recent works have led to a…
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