86 citations · 174 across the 29 of their papers we have counts for
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physics.chem-ph2022★ 1 cited
Soft and transferable pseudopotentials from multi-objective optimization
Mostafa Faghih Shojaei, John E. Pask, Andrew J. Medford +1
Ab initio pseudopotentials are a linchpin of modern molecular and condensed matter electronic structure calculations. In this work, we employ multi-objective optimization to maximi…
physics.chem-ph2022★ 2 cited
Robust and scalable uncertainty estimation with conformal prediction for machine-learned interatomic potentials
Yuge Hu, Joseph Musielewicz, Zachary Ulissi +1
Uncertainty quantification (UQ) is important to machine learning (ML) force fields to assess the level of confidence during prediction, as ML models are not inherently physical and…