94 citations · 182 across the 5 of their papers we have counts for
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cs.LG2023★ 94 cited
Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles
Aik Rui Tan, Shingo Urata, Samuel Goldman +2
Neural networks (NNs) often assign high confidence to their predictions, even for points far out-of-distribution, making uncertainty quantification (UQ) a challenge. When they are…
cond-mat.mtrl-sci2023
Representations of Materials for Machine Learning
James Damewood, Jessica Karaguesian, Jaclyn R. Lunger +4
High-throughput data generation methods and machine learning (ML) algorithms have given rise to a new era of computational materials science by learning relationships among composi…