1 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Bridging Geometric States via Geometric Diffusion Bridge
Shengjie Luo, Yixian Xu, Di He +3
The accurate prediction of geometric state evolution in complex systems is critical for advancing scientific domains such as quantum chemistry and material modeling. Traditional ex…
cs.LG2024
GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
Tianlang Chen, Shengjie Luo, Di He +3
Molecular modeling, a central topic in quantum mechanics, aims to accurately calculate the properties and simulate the behaviors of molecular systems. The molecular model is govern…
physics.comp-ph2023★ 1 cited
Forward Laplacian: A New Computational Framework for Neural Network-based Variational Monte Carlo
Ruichen Li, Haotian Ye, Du Jiang +8
Neural network-based variational Monte Carlo (NN-VMC) has emerged as a promising cutting-edge technique of ab initio quantum chemistry. However, the high computational cost of exis…