2 citations · 2 across the 1 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2026★ 2 cited
Generative Models for Crystalline Materials
Houssam Metni, Laura Ruple, Lauren N. Walters +13
Understanding structure-property relationships in materials is fundamental in condensed matter physics and materials science. Over the past few years, machine learning (ML) has eme…
cs.LG2024
PAL -- Parallel active learning for machine-learned potentials
Chen Zhou, Marlen Neubert, Yuri Koide +5
Constructing datasets representative of the target domain is essential for training effective machine learning models. Active learning (AL) is a promising method that iteratively e…