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most citedGraph-neural-network predictions of solid-state NMR parameters from spherical tensor decomposition

8 citations · 19 across the 6 of their papers we have counts for

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physics.comp-ph2025★ 7 cited

Distillation of atomistic foundation models across architectures and chemical domains

John L. A. Gardner, Daniel F. Thomas du Toit, Chiheb Ben Mahmoud +8

Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trai…