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 ...
In this paper, we instantiate this idea with local scaling transformation as an example showing how to construct neural-based wave functions for DFT. 2 DFT ...
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 ...
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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 ...
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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 ...
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 the total energy ...
Mar 3, 2023 · D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory. "We directly minimize the total energy by reparameterizing the ...
@inproceedings{li2023d4ft, title={D4FT: A Deep Learning Approach to Kohn-Sham Density Functional Theory}, author={Li, Tianbo and Lin, Min and Hu, Zheyuan ...
Mar 1, 2023 · Kohn-Sham Density Functional Theory (KS-DFT) has been traditionally solved by the Self-Consistent Field (SCF) method. Numerical Integration ...