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Found 2 papers, 1 papers with code
LTAU-FF: Loss Trajectory Analysis for Uncertainty in Atomistic Force Fields
Though in this work we focus on the use of LTAU with deep learning atomistic force fields, we emphasize that it can be readily applied to any regression task, or any ensemble-generation technique, to provide a reliable and easy-to-implement UQ metric.
Predicting phase behavior of grain boundaries with evolutionary search and machine learning
The study of grain boundary phase transitions is an emerging field until recently dominated by experiments.
Materials Science
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