274 citations · 1.2k across the 26 of their papers we have counts for
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physics.chem-ph2025★ 5 cited
Multi-head committees enable direct uncertainty prediction for atomistic foundation models
Hubert Beck, Pavol Simko, Lars L. Schaaf +2
Machine learning potentials have become a standard tool for atomistic materials modelling. While models continue to become more generalisable, an open challenge relates to efficien…
physics.comp-ph2025★ 1 cited
The CP2K Program Package Made Simple
Marcella Iannuzzi, Jan Wilhelm, Frederick Stein +24
CP2K is a versatile open-source software package for simulations across a wide range of atomistic systems, from isolated molecules in the gas phase to low-dimensional functional ma…