3 papers
physics.chem-ph2025
Node-Equivariant Message Passing for Efficient and Accurate Machine Learning Interatomic Potentials
Yaolong Zhang, Hua Guo
Machine learned interatomic potentials, particularly equivariant message-passing (MP) models, have demonstrated high fidelity in representing first-principles data, revolutionizing…
physics.chem-ph2025
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…
physics.chem-ph2024
SchrödingerNet: A Universal Neural Network Solver for The Schrödinger Equation
Yaolong Zhang, Bin Jiang, Hua Guo
Recent advances in machine learning have facilitated numerically accurate solution of the electronic Schrödinger equation (SE) by integrating various neural network (NN)-based wav…