308 citations · 600 across the 4 of their papers we have counts for
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physics.chem-ph2020★ 101 cited
Uncertainty estimation for molecular dynamics and sampling
Giulio Imbalzano, Yongbin Zhuang, Venkat Kapil +4
Machine learning models have emerged as a very effective strategy to sidestep time-consuming electronic-structure calculations, enabling accurate simulations of greater size, time…
physics.comp-ph2020
The role of feature space in atomistic learning
Alexander Goscinski, Guillaume Fraux, Giulio Imbalzano +1
Eficient, physically-inspired descriptors of the structure and composition of molecules and materials play a key role in the application of machine-learning techniques to atomistic…