A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions-Reference-Cited by-同舟云学术

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A Kaczmarz-inspired approach to accelerate the optimization of neural network wavefunctions

Published:2024-11 Issue: Volume:516 Page:113351
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Goldshlager Gil^ORCID,Abrahamsen Nilin,Lin Lin

Funder

US Department of Energy

Office of Naval Research

Publisher

Elsevier BV

Reference44 articles.

1. Quantum Monte Carlo simulations of solids;Foulkes;Rev. Mod. Phys.,2001

2. Quantum Monte Carlo Approaches for Correlated Systems;Federico,2017

3. Ab initio solution of the many-electron Schrödinger equation with deep neural networks;Pfau;Phys. Rev. Res.,2020

4. Deep-neural-network solution of the electronic Schrödinger equation;Hermann;Nat. Chem.,2020

5. Deepqmc: an open-source software suite for variational optimization of deep-learning molecular wave functions;Schätzle;J. Chem. Phys.,2023

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