84 citations · 166 across the 12 of their papers we have counts for
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cond-mat.mtrl-sci2024
When More Data Hurts: Optimizing Data Coverage While Mitigating Diversity Induced Underfitting in an Ultra-Fast Machine-Learned Potential
Jason B. Gibson, Tesia D. Janicki, Ajinkya C. Hire +3
Machine-learned interatomic potentials (MLIPs) are becoming an essential tool in materials modeling. However, optimizing the generation of training data used to parameterize the ML…
cond-mat.mtrl-sci2020★ 3 cited
Remarkable low-energy properties of the pseudogapped semimetal BePt
L. Fanfarillo, J. J. Hamlin, R. G. Hennig +7
We report measurements and calculations on the properties of the intermetallic compound BePt. High-quality polycrystalline samples show a nearly constant temperature dependence…