4 citations · 9 across the 9 of their papers we have counts for
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physics.comp-ph2024★ 2 cited
Learning charges and long-range interactions from energies and forces
Dongjin Kim, Daniel S. King, Peichen Zhong +1
Accurate modeling of long-range forces is critical in atomistic simulations, as they play a central role in determining the properties of materials and chemical systems. However, s…
cs.LG2024★ 1 cited
Latent Ewald summation for machine learning of long-range interactions
Bingqing Cheng
Machine learning interatomic potentials (MLIPs) often neglect long-range interactions, such as electrostatic and dispersion forces. In this work, we introduce a straightforward and…