63 citations · 80 across the 9 of their papers we have counts for
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cond-mat.mtrl-sci2026★ 2 cited
High-quality, high-information datasets for universal atomistic machine learning
Cesare Malosso, Filippo Bigi, Paolo Pegolo +7
The quality, consistency, and information content of training data is often what determines the practical value of machine-learning models for atomistic simulations. Yet, many wide…
cond-mat.mtrl-sci2022★ 63 cited
Viscosity in water from first-principles and deep-neural-network simulations
Cesare Malosso, Linfeng Zhang, Roberto Car +2
We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio mol…