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20202023
most citedLearning Together: Towards foundational models for machine learning interatomic potentials with meta-learning

5 citations · 6 across the 3 of their papers we have counts for

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physics.chem-ph2023★ 5 cited

Learning Together: Towards foundational models for machine learning interatomic potentials with meta-learning

Alice E. A. Allen, Nicholas Lubbers, Sakib Matin +4

The development of machine learning models has led to an abundance of datasets containing quantum mechanical (QM) calculations for molecular and material systems. However, traditio…

physics.chem-ph2020

Atomic Permutationally Invariant Polynomials for Fitting Molecular Force Fields

Alice Allen, Gábor Csányi, Geneviève Dusson +1

We introduce and explore an approach for constructing force fields for small molecules, which combines intuitive low body order empirical force field terms with the concepts of dat…