7 citations · 13 across the 4 of their papers we have counts for
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cond-mat.mtrl-sci2022★ 5 cited
Shared Metadata for Data-Centric Materials Science
Luca M. Ghiringhelli, Carsten Baldauf, Tristan Bereau +32
The expansive production of data in materials science, their widespread sharing and repurposing requires educated support and stewardship. In order to ensure that this need helps r…
cond-mat.mtrl-sci2022
Convergence Acceleration in Machine Learning Potentials for Atomistic Simulations
Dylan Bayerl, Christopher M. Andolina, Shyam Dwaraknath +1
Machine learning potentials (MLPs) for atomistic simulations have an enormous prospective impact on materials modeling, offering orders of magnitude speedup over density functional…