| Deep-learning density functional theory Hamiltonian for efficient ab initio electronic-structure calculation H Li, Z Wang, N Zou, M Ye, R Xu, X Gong, W Duan, Y Xu Nature Computational Science 2 (6), 367-377, 2022 | 89 | 2022 |
| General framework for E (3)-equivariant neural network representation of density functional theory Hamiltonian X Gong, H Li, N Zou, R Xu, W Duan, Y Xu Nature Communications 14 (1), 2848, 2023 | 29 | 2023 |
| Deep-learning electronic-structure calculation of magnetic superstructures H Li, Z Tang, X Gong, N Zou, W Duan, Y Xu Nature Computational Science 3 (4), 321-327, 2023 | 16 | 2023 |
| Efficient hybrid density functional calculation by deep learning Z Tang, H Li, P Lin, X Gong, G Jin, L He, H Jiang, X Ren, W Duan, Y Xu arXiv preprint arXiv:2302.08221, 2023 | 3 | 2023 |
| Deep-learning density functional perturbation theory H Li, Z Tang, J Fu, WH Dong, N Zou, X Gong, W Duan, Y Xu Physical Review Letters 132 (9), 096401, 2024 | 2 | 2024 |
| DeepH-2: Enhancing deep-learning electronic structure via an equivariant local-coordinate transformer Y Wang, H Li, Z Tang, H Tao, Y Wang, Z Yuan, Z Chen, W Duan, Y Xu arXiv preprint arXiv:2401.17015, 2024 | 2 | 2024 |
| Equivariant neural network force fields for magnetic materials Z Yuan, Z Xu, H Li, X Cheng, H Tao, Z Tang, Z Zhou, W Duan, Y Xu Quantum Frontiers 3 (1), 8, 2024 | 1 | 2024 |
| Ab initio artificial intelligence: Future research of Materials Genome Initiative H Li, Y Xu, W Duan Materials Genome Engineering Advances 1 (2), e16, 2023 | 1 | 2023 |
| Deep-Learning Database of Density Functional Theory Hamiltonians for Twisted Materials T Bao, R Xu, H Li, X Gong, Z Tang, J Fu, W Duan, Y Xu arXiv preprint arXiv:2404.06449, 2024 | | 2024 |
| Neural-network density functional theory Y Li, Z Tang, Z Chen, M Sun, B Zhao, H Li, H Tao, Z Yuan, W Duan, Y Xu arXiv preprint arXiv:2403.11287, 2024 | | 2024 |
