Learning the exchange-correlation functional from nature with fully differentiable density functional theory
Improving the predictive capability of molecular properties in ab initio simulations is essential for advanced material discovery. Despite recent progress making use of machine learning, utilizing deep neural networks to improve quantum chemistry modeling remains severely limited by the scarcity and...
| Main Authors: | , |
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| Format: | Journal article |
| Language: | English |
| Published: |
American Physical Society
2021
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