4 citations · 4 across the 3 of their papers we have counts for
3 papers
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…
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…
Machine learning for rapid discovery of laminar flow channel wall modifications that enhance heat transfer
Yuri Koide, Arjun J. Kaithakkal, Matthias Schniewind +3
Numerical simulation of fluids plays an essential role in modeling many physical phenomena, which enables technological advancements, contributes to sustainable practices, and expa…