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20122026
most citedE(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials

1.9k citations · 2k across the 11 of their papers we have counts for

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Showing 2022Show all

2 papers · 1 filter

physics.comp-ph2022★ 2 cited

Orbital Mixer: Using Atomic Orbital Features for Basis Dependent Prediction of Molecular Wavefunctions

Kirill Shmilovich, Devin Willmott, Ivan Batalov +3

Leveraging ab initio data at scale has enabled the development of machine learning models capable of extremely accurate and fast molecular property prediction. A central paradigm o…

physics.comp-ph2022★ 22 cited

Learning Local Equivariant Representations for Large-Scale Atomistic Dynamics

Albert Musaelian, Simon Batzner, Anders Johansson +4

A simultaneously accurate and computationally efficient parametrization of the energy and atomic forces of molecules and materials is a long-standing goal in the natural sciences.…