6 citations · 7 across the 4 of their papers we have counts for
5 papers
Towards stable and accurate electron dynamics via neural network based time-dependent variational Monte Carlo
Weizhong Fu, Zhe Li, Yubing Qian +3
Real-time dynamics of interacting electrons lies at the interface between quantum mechanics and non-equilibrium physics, governing the microscopic origin of ultrafast phenomena of…
A particle view of many-body electronic structure with neural network wavefunction
Zichen Wang, Weizhong Fu, Zhe Li +2
In the study of electronic structure, the wavefunction view dominates the current research landscape and forms the theoretical foundation of modern quantum mechanics. In contrast,…
Deep learning quantum Monte Carlo for solids
Yubing Qian, Xiang Li, Zhe Li +2
Deep learning has deeply changed the paradigms of many research fields. At the heart of chemical and physical sciences is the accurate ab initio calculation of many-body wavefuncti…
Symmetry enforced solution of the many-body Schrödinger equation with deep neural network
Zhe Li, Zixiang Lu, Ruichen Li +5
The integration of deep neural networks with the Variational Monte Carlo (VMC) method has marked a significant advancement in solving the Schrödinger equation. In this work, we enf…
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…