75 citations · 163 across the 10 of their papers we have counts for
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physics.comp-ph2024★ 7 cited
Understanding the wetting of transition metal dichalcogenides from an ab initio perspective
Siheng Li, Keyang Liu, Jiří Klimeš +1
Transition metal dichalcogenides (TMDs) are a class of two-dimensional (2D) materials been widely studied for emerging electronic properties. In this work, we use computational sim…
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…