103 citations · 216 across the 8 of their papers we have counts for
Showing 2022 · physics.comp-phShow all
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physics.comp-ph2022★ 74 cited
Fast Uncertainty Estimates in Deep Learning Interatomic Potentials
Albert Zhu, Simon Batzner, Albert Musaelian +1
Deep learning has emerged as a promising paradigm to give access to highly accurate predictions of molecular and materials properties. A common short-coming shared by current appro…
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.…