63 citations · 114 across the 20 of their papers we have counts for
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physics.chem-ph2023★ 9 cited
Electric Polarization from Many-Body Neural Network Ansatz
Xiang Li, Yubing Qian, Ji Chen
Ab initio calculation of dielectric response with high-accuracy electronic structure methods is a long-standing problem, for which mean-field approaches are widely used and electro…
physics.comp-ph2023★ 1 cited
Variance extrapolation method for neural-network variational Monte Carlo
Weizhong Fu, Weiluo Ren, Ji Chen
Constructing more expressive ansatz has been a primary focus for quantum Monte Carlo, aimed at more accurate \textit{ab initio} calculations. However, with more powerful ansatz, e.…
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…