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20222026
most citedA Statistical Perspective for Predicting the Strength of Metals: Revisiting the Hall-Petch Relationship using Machine Learning

30 citations · 39 across the 8 of their papers we have counts for

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cs.LG2024★ 1 cited

Self-supervised learning for crystal property prediction via denoising

Alexander New, Nam Q. Le, Michael J. Pekala +1

Accurate prediction of the properties of crystalline materials is crucial for targeted discovery, and this prediction is increasingly done with data-driven models. However, for man…

cs.LG2022

Curvature-informed multi-task learning for graph networks

Alexander New, Michael J. Pekala, Nam Q. Le +3

Properties of interest for crystals and molecules, such as band gap, elasticity, and solubility, are generally related to each other: they are governed by the same underlying laws…