Higher model accuracy improves uncertainty-error correlation and novelty detection in MLIP UQ, and clustering-enhanced local D-optimality better detects novel environments on heterogeneous datasets.
Jacobs, et al., A practical guide to machine learning interatomic potentials--Status and future
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cond-mat.mtrl-sci 1years
2025 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Model Accuracy and Data Heterogeneity Shape Uncertainty Quantification in Machine Learning Interatomic Potentials
Higher model accuracy improves uncertainty-error correlation and novelty detection in MLIP UQ, and clustering-enhanced local D-optimality better detects novel environments on heterogeneous datasets.