Solving high-dimensional eigenvalue problems using deep neural networks: a diffusion Monte Carlo like approach
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Publication:2123831
DOI10.1016/j.jcp.2020.109792OpenAlexW3004547276MaRDI QIDQ2123831
Jiequn Han, Mo Zhou, Jian-feng Lu
Publication date: 14 April 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2002.02600
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Uses Software
Cites Work
- Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations
- The Deep Ritz Method: a deep learning-based numerical algorithm for solving variational problems
- Solving many-electron Schrödinger equation using deep neural networks
- Structure of a quantized vortex in boson systems
- Solving high-dimensional partial differential equations using deep learning
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