Johannes Gasteiger, Florian Becker, and Stephan Gunnemann. GemNet: Universal directional graph neural networks for molecules. Advances in Neural Information Processing Systems, 34: 6790-6802, 2021.
Mario Geiger, Tess Smidt, Alby M., Benjamin Kurt Miller, Wouter Boomsma, Bradley Dice, Kostiantyn Lapchevskyi, Maurice Weiler, Michal Tyszkiewicz, Simon Batzner, Dylan Madisetti, Martin Uhrin, Jes Frellsen, Nuri Jung, Sophia Sanborn, Mingjian Wen, Josh Rackers, Marcel Rød, and Michael Bailey. Euclidean neural networks: e3nn, April 2022. URL https://doi.org/10.5281/zenodo.6459381.
Xiaoxun Gong, He Li, Nianlong Zou, Runzhang Xu, Wenhui Duan, and Yong Xu. General framework for E(3)-equivariant neural network representation of density functional theory Hamiltonian. Nature Communications, 14(1):2848, 2023.
P. Hohenberg and W. Kohn. Inhomogeneous electron gas. Phys. Rev., 136:B864-B871, Nov 1964. doi: 10.1103/PhysRev.136.B864. URL https://link.aps.org/doi/10.1103/PhysRev.136.B864.
Bing Huang, Guido Falk von Rudorff, and O Anatole von Lilienfeld. The central role of density functional theory in the ai age. Science, 381(6654):170-175, 2023.
Kuzma Khrabrov, Ilya Shenbin, Alexander Ryabov, Artem Tsypin, Alexander Telepov, Anton Alekseev, Alexander Grishin, Pavel Strashnov, Petr Zhilyaev, Sergey Nikolenko, et al. nabladft: Large-scale conformational energy and hamiltonian prediction benchmark and dataset. Physical Chemistry Chemical Physics, 24(42):25853-25863, 2022.
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu, et al. PubChem 2019 update: improved access to chemical data. Nucleic Acids Research, 47(D1):D1102-D1109, 2019.
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu, et al. PubChem in 2021: new data content and improved web interfaces. *Nucleic Acids Research*, 49(D1):D1388–D1395, 2021.
Sunghwan Kim, Jie Chen, Tiejun Cheng, Asta Gindulyte, Jia He, Siqian He, Qingliang Li, Benjamin A Shoemaker, Paul A Thiessen, Bo Yu, et al. PubChem 2023 update. Nucleic Acids Research, 51 (D1):D1373–D1380, 2023.
James Kirkpatrick, Brendan McMorrow, David HP Turban, Alexander L Gaunt, James S Spencer, Alexander GDG Matthews, Annette Obika, Louis Thiry, Meire Fortunato, David Pfau, et al. Pushing the frontiers of density functionals by solving the fractional electron problem. Science, 374(6573):1385-1389, 2021.
W. Kohn and L. J. Sham. Self-consistent equations including exchange and correlation effects. Phys. Rev., 140:A1133-A1138, Nov 1965. doi: 10.1103/PhysRev.140.A1133. URL https://link.aps.org/doi/10.1103/PhysRev.140.A1133.
Dávid Péter Kovács, Cas van der Oord, Jiri Kucera, Alice EA Allen, Daniel J Cole, Christoph Ortner, and Gábor Csányi. Linear Atomic Cluster Expansion Force Fields for Organic Molecules: Beyond RMSE. Journal of Chemical Theory and Computation, 17(12):7696-7711, 2021.
Chengteh Lee, Weitao Yang, and Robert G. Parr. Development of the colle-salvetti correlation-energy formula into a functional of the electron density. Phys. Rev. B, 37:785-789, Jan 1988. doi: 10.1103/PhysRevB.37.785. URL https://link.aps.org/doi/10.1103/PhysRevB.37.785.
He Li, Zun Wang, Nianlong Zou, Meng Ye, Runzhang Xu, Xiaoxun Gong, Wenhui Duan, and Yong Xu. Deep-learning density functional theory hamiltonian for efficient ab initio electronic-structure calculation. Nature Computational Science, 2(6):367-377, 2022.
He Li, Zechen Tang, Xiaoxun Gong, Nianlong Zou, Wenhui Duan, and Yong Xu. Deep-learning electronic-structure calculation of magnetic superstructures. Nature Computational Science, 3(4): 321-327, 2023.