3 citations · 9 across the 9 of their papers we have counts for
9 papers
Spin-Adapted Neural Network Wavefunctions in Real Space
Ruichen Li, Yuzhi Liu, Du Jiang +7
Spin plays a fundamental role in understanding electronic structure, yet many real-space wavefunction methods fail to adequately consider it. We introduce the Spin-Adapted Antisymm…
Neural Scaling Laws Surpass Chemical Accuracy for the Many-Electron Schrödinger Equation
Du Jiang, Xuelan Wen, Yixiao Chen +8
We demonstrate, for the first time, that neural scaling laws can deliver near-exact solutions to the many-electron Schrödinger equation across a broad range of realistic molecules.…
Solving the Hubbard model with Neural Quantum States
Yuntian Gu, Wenrui Li, Heng Lin +9
The rapid development of neural quantum states (NQS) has established it as a promising framework for studying quantum many-body systems. In this work, by leveraging the cutting-edg…
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…
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…
Representation of General Continuous Anti-symmetric Function
Haotian Ye, Ruichen Li, Yuntian Gu +3
In quantum mechanics, the wave function of fermion systems such as many-body electron systems are anti-symmetric (AS) and continuous, and it is crucial yet challenging to find an a…
DOF: Accelerating High-order Differential Operators with Forward Propagation
Ruichen Li, Chuwei Wang, Haotian Ye +2
Solving partial differential equations (PDEs) efficiently is essential for analyzing complex physical systems. Recent advancements in leveraging deep learning for solving PDE have…
Deep Learning with Information Fusion and Model Interpretation for Health Monitoring of Fetus based on Long-term Prenatal Electronic Fetal Heart Rate Monitoring Data
Zenghui Lin, Xintong Liu, Nan Wang +6
Long-term fetal heart rate (FHR) monitoring during the antepartum period, increasingly popularized by electronic FHR monitoring, represents a growing approach in FHR monitoring. Th…
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…