| ASGN: An active semi-supervised graph neural network for molecular property prediction Z Hao, C Lu, Z Huang, H Wang, Z Hu, Q Liu, E Chen, C Lee Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020 | 138 | 2020 |
| Physics-informed machine learning: A survey on problems, methods and applications Z Hao, S Liu, Y Zhang, C Ying, Y Feng, H Su, J Zhu arXiv preprint arXiv:2211.08064, 2022 | 101 | 2022 |
| A two-stage 3D CNN based learning method for spontaneous micro-expression recognition S Zhao, H Tao, Y Zhang, T Xu, K Zhang, Z Hao, E Chen Neurocomputing 448, 276-289, 2021 | 83 | 2021 |
| Gnot: A general neural operator transformer for operator learning Z Hao, C Ying, Z Wang, H Su, Y Dong, S Liu, Z Cheng, J Zhu, J Song International Conference on Machine Learning (ICML 2023), 2023 | 60 | 2023 |
| Equivariant Energy-Guided SDE for Inverse Molecular Design F Bao, M Zhao, Z Hao, P Li, C Li, J Zhu International Conference on Learning Representations (ICLR 2023), 2023 | 38 | 2023 |
| GSmooth: Certified Robustness against Semantic Transformations via Generalized Randomized Smoothing Z Hao, C Ying, Y Dong, H Su, J Zhu, J Song International Conference on Machine Learning (ICML 2022), 2022 | 23 | 2022 |
| A unified hard-constraint framework for solving geometrically complex pdes S Liu, H Zhongkai, C Ying, H Su, J Zhu, Z Cheng Advances in Neural Information Processing Systems 35, 20287-20299, 2022 | 17 | 2022 |
| Pinnacle: A comprehensive benchmark of physics-informed neural networks for solving pdes Z Hao, J Yao, C Su, H Su, Z Wang, F Lu, Z Xia, Y Zhang, S Liu, L Lu, J Zhu arXiv preprint arXiv:2306.08827, 2023 | 15 | 2023 |
| Bi-level physics-informed neural networks for pde constrained optimization using broyden's hypergradients Z Hao, C Ying, H Su, J Zhu, J Song, Z Cheng International Conference on Learning Representations (ICLR 2023), 2022 | 9 | 2022 |
| CLUSTER ATTACK: Query-based Adversarial Attacks on Graphs with Graph-Dependent Priors Z Wang, Z Hao, Z Wang, H Su, J Zhu IJCAI 2022, 0 | 9* | |
| Full-atom protein pocket design via iterative refinement Z Zhang, Z Lu, H Zhongkai, M Zitnik, Q Liu Advances in Neural Information Processing Systems 36, 16816-16836, 2023 | 8 | 2023 |
| Your diffusion model is secretly a certifiably robust classifier H Chen, Y Dong, S Shao, Z Hao, X Yang, H Su, J Zhu arXiv preprint arXiv:2402.02316, 2024 | 7 | 2024 |
| MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks J Yao, C Su, Z Hao, S Liu, H Su, J Zhu International Conference on Machine Learning (ICML 2023), 2023 | 7 | 2023 |
| Reward informed dreamer for task generalization in reinforcement learning C Ying, Z Hao, X Zhou, H Su, S Liu, J Li, D Yan, J Zhu arXiv preprint arXiv:2303.05092, 2023 | 7 | 2023 |
| NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data S Liu, Z Hao, C Ying, H Su, Z Cheng, J Zhu International Conference on Machine Learning (ICML 2023), 2023 | 5 | 2023 |
| Avt: Au-assisted visual transformer for facial expression recognition R Jin, S Zhao, Z Hao, Y Xu, T Xu, E Chen 2022 IEEE International Conference on Image Processing (ICIP), 2661-2665, 2022 | 5 | 2022 |
| Physics-Informed Machine Learning: A Survey on Problems Z Hao, S Liu, Y Zhang, C Ying, Y Feng, H Su, J Zhu Methods and Applications. arXiv 2211, 2022 | 5 | 2022 |
| Dpot: Auto-regressive denoising operator transformer for large-scale pde pre-training Z Hao, C Su, S Liu, J Berner, C Ying, H Su, A Anandkumar, J Song, J Zhu arXiv preprint arXiv:2403.03542, 2024 | 4 | 2024 |
| Preconditioning for physics-informed neural networks S Liu, C Su, J Yao, Z Hao, H Su, Y Wu, J Zhu arXiv preprint arXiv:2402.00531, 2024 | 3 | 2024 |
| Improved operator learning by orthogonal attention Z Xiao, Z Hao, B Lin, Z Deng, H Su arXiv preprint arXiv:2310.12487, 2023 | 3 | 2023 |
Hang SuAssociated Professor, Tsinghua UniversityPatvirtintas el. paštas mail.tsinghua.edu.cn
