Mar 1, 2023 · We propose a deep learning approach to KS-DFT. First, in contrast to the conventional SCF loop, we propose to directly minimize the total energy.
Density functional theory (DFT) is the most successful quantum-mechanical method, which is widely used in chemistry and physics for predicting electron-related ...
Mar 1, 2023 · In this work, we propose a deep learning approach to KS-DFT. First, in contrast to the conventional SCF loop, we propose to directly minimize ...
Mar 1, 2023 · In this work, we propose a deep-learning approach to KS-DFT. First, in contrast to the conventional SCF loop, we propose directly minimizing the ...
D4FT aims to provide atomic APIs similar to modern deep learning library like Jax and Pytorch, so that developers can easily write new algorithm by composing ...
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Mar 1, 2023 · Kohn-Sham Density Functional Theory (KS-DFT) has been traditionally solved by the Self-Consistent Field (SCF) method. Numerical Integration.
Mar 1, 2023 · In this work, we propose a deep learning approach to KS-DFT. First, in contrast to the conventional SCF loop, we propose directly minimizing the ...
@inproceedings{li2023d4ft, title={D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory}, author={Li, Tianbo and Lin, Min and Hu, Zheyuan ...
Explore all code implementations available for D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory.
D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. Tianbo Li · Min Lin · Zheyuan Hu · Kunhao Zheng · Giovanni Vignale · Kenji Kawaguchi ...