178 citations · 685 across the 15 of their papers we have counts for
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cond-mat.mtrl-sci2022★ 4 cited
Capturing long-range interaction with reciprocal space neural network
Hongyu Yu, Liangliang Hong, Shiyou Chen +2
Machine Learning (ML) interatomic models and potentials have been widely employed in simulations of materials. Long-range interactions often dominate in some ionic systems whose dy…
cond-mat.mtrl-sci2022★ 12 cited
General time-reversal equivariant neural network potential for magnetic materials
Hongyu Yu, Boyu Liu, Yang Zhong +5
This study introduces time-reversal E(3)-equivariant neural network and SpinGNN++ framework for constructing a comprehensive interatomic potential for magnetic systems, encompassin…
physics.comp-ph2022★ 52 cited
Spin-Dependent Graph Neural Network Potential for Magnetic Materials
Hongyu Yu, Yang Zhong, Liangliang Hong +4
The development of machine learning interatomic potentials has immensely contributed to the accuracy of simulations of molecules and crystals. However, creating interatomic potenti…