129 citations · 188 across the 7 of their papers we have counts for
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cond-mat.mtrl-sci2023★ 2 cited
Understanding defects in amorphous silicon with million-atom simulations and machine learning
Joe D. Morrow, Chinonso Ugwumadu, David A. Drabold +3
The structure of amorphous silicon is widely thought of as a fourfold-connected random network, and yet it is defective atoms, with fewer or more than four bonds, that make it part…
physics.chem-ph2023★ 33 cited
Robustness of Local Predictions in Atomistic Machine Learning Models
Sanggyu Chong, Federico Grasselli, Chiheb Ben Mahmoud +3
Machine learning (ML) models for molecules and materials commonly rely on a decomposition of the global target quantity into local, atom-centered contributions. This approach is co…