11 citations · 29 across the 8 of their papers we have counts for
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physics.chem-ph2025
Empowering Neural Network-based Quantum Monte Carlo with Local Pseudopotentials
Weizhong Fu, Ryunosuke Fujimaru, Ruichen Li +9
Neural Network-based Quantum Monte Carlo (NNQMC), an emerging method for solving many-body quantum systems with high accuracy, has been mainly applied to small systems due to deman…
physics.chem-ph2024★ 6 cited
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…
physics.chem-ph2024
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…