| Self-supervised learning of graph neural networks: A unified review Y Xie, Z Xu, J Zhang, Z Wang, S Ji IEEE transactions on pattern analysis and machine intelligence 45 (2), 2412-2429, 2022 | 445 | 2022 |
| DIG: A Turnkey Library for Diving into Graph Deep Learning Research M Liu, Y Luo, L Wang, Y Xie, H Yuan, S Gui, H Yu, Z Xu, J Zhang, Y Liu, ... Journal of Machine Learning Research 22 (240), 1-9, 2021 | 148* | 2021 |
| Artificial intelligence for science in quantum, atomistic, and continuum systems X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ... arXiv preprint arXiv:2307.08423, 2023 | 127 | 2023 |
| Advanced graph and sequence neural networks for molecular property prediction and drug discovery Z Wang, M Liu, Y Luo, Z Xu, Y Xie, L Wang, L Cai, Q Qi, Z Yuan, T Yang, ... Bioinformatics 38 (9), 2579-2586, 2022 | 124 | 2022 |
| Stochastic Optimization of Area Under Precision-Recall Curve for Deep Learning with Provable Convergence Q Qi, Y Luo, Z Xu, S Ji, T Yang Advances in Neural Information Processing Systems 34, 2021 | 86 | 2021 |
| A text-guided protein design framework S Liu, Y Li, Z Li, A Gitter, Y Zhu, J Lu, Z Xu, W Nie, A Ramanathan, C Xiao, ... arXiv preprint arXiv:2302.04611, 2023 | 62 | 2023 |
| Self-Supervised Representation Learning via Latent Graph Prediction Y Xie, Z Xu, S Ji Proceedings of the 39th International Conference on Machine Learning, 24460 …, 2022 | 39 | 2022 |
| Molecule3d: A benchmark for predicting 3d geometries from molecular graphs Z Xu, Y Luo, X Zhang, X Xu, Y Xie, M Liu, K Dickerson, C Deng, M Nakata, ... arXiv preprint arXiv:2110.01717, 2021 | 38 | 2021 |
| Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian H Yu, Z Xu, X Qian, X Qian, S Ji Proceedings of the 40th International Conference on Machine Learning, 2023 | 24 | 2023 |
| Fast quantum property prediction via deeper 2d and 3d graph networks M Liu, C Fu, X Zhang, L Wang, Y Xie, H Yuan, Y Luo, Z Xu, S Xu, S Ji NeurIPS 2021 AI for Science Workshop, 2021, 2021 | 14 | 2021 |
| 3D Molecular Geometry Analysis with 2D Graphs Z Xu, Y Xie, Y Luo, X Zhang, X Xu, M Liu, K Dickerson, C Deng, M Nakata, ... Proceedings of the 2024 SIAM International Conference on Data Mining (SDM …, 2024 | 3 | 2024 |
| Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction Z Xu, H Yu, M Bohde, S Ji Transactions on Machine Learning Research, 2024 | | 2024 |
| Mining the Metabolic Capacity of Clostridium sporogenes Aided by Machine Learning H Ouyang, Z Xu, J Hong, J Malroy, L Qian, S Ji, X Zhu Angewandte Chemie International Edition 63 (12), e202319925, 2024 | | 2024 |
| Frontiers of Graph Neural Networks with DIG S Ji, M Liu, Y Liu, Y Luo, L Wang, Y Xie, Z Xu, H Yu Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | | 2022 |
Shuiwang Ji, Professor and Truchard...Department of Computer Science & Engineering, Texas A&M UniversityPotvrđena adresa e-pošte na tamu.edu
