Autoregressive neural Slater-Jastrow ansatz for variational Monte Carlo simulation
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Publication:6594488
DOI10.21468/scipostphys.14.6.171MaRDI QIDQ6594488
Stephan Humeniuk, Lei Wang, Yuan Wan
Publication date: 28 August 2024
Published in: SciPost Physics (Search for Journal in Brave)
Artificial neural networks and deep learning (68T07) Monte Carlo methods (65C05) Other fundamental interactions in quantum theory (81V19)
Cites Work
- Unnamed Item
- Solving many-electron Schrödinger equation using deep neural networks
- Determinantal Point Processes for Machine Learning
- Training Products of Experts by Minimizing Contrastive Divergence
- Many-Body Problem with Strong Forces
- Solving the quantum many-body problem with artificial neural networks
- Quantum Monte Carlo Approaches for Correlated Systems
- mVMC -- open-source software for many-variable variational Monte Carlo method
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