64 citations · 64 across the 3 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
physics.chem-ph2025
Efficient Parallelization of Message Passing Neural Network Potentials for Large-scale Molecular Dynamics
Junfan Xia, Bin Jiang
Machine learning potentials have achieved great success in accelerating atomistic simulations. Many of them relying on atom-centered local descriptors are natural for parallelizati…
physics.chem-ph2025★ 64 cited
The Evolution of Machine Learning Potentials for Molecules, Reactions and Materials
Junfan Xia, Yaolong Zhang, Bin Jiang
Recent years have witnessed the fast development of machine learning potentials (MLPs) and their widespread applications in chemistry, physics, and material science. By fitting dis…