| Self-supervised learning on graphs: Contrastive, generative, or predictive L Wu, H Lin, C Tan, Z Gao, SZ Li TKDE 2022 - IEEE Transactions on Knowledge and Data Engineering, 2021 | 282 | 2021 |
| SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation J Xia*, L Wu*, J Chen, B Hu, SZ Li WWW 2022 - The Web Conference (Most Influential WWW Papers), 2022 | 254 | 2022 |
| Simvp: Simpler yet better video prediction Z Gao, C Tan, L Wu, SZ Li CVPR 2022 - IEEE/CVF Conference on Computer Vision and Pattern Recognition …, 2022 | 194 | 2022 |
| Progcl: Rethinking hard negative mining in graph contrastive learning J Xia, L Wu, G Wang, J Chen, SZ Li ICML 2022 - International Conference on Machine Learning, 2022 | 124 | 2022 |
| Co-learning: Learning from noisy labels with self-supervision C Tan, J Xia, L Wu, SZ Li ACM MM 2021 - ACM International Conference on Multimedia, 2021 | 113 | 2021 |
| Automix: Unveiling the power of mixup for stronger classifiers Z Liu, S Li, D Wu, Z Liu, Z Chen, L Wu, SZ Li ECCV 2022 - European Conference on Computer Vision, 441-458, 2022 | 83 | 2022 |
| Graphmixup: Improving class-imbalanced node classification by reinforcement mixup and self-supervised context prediction L Wu*, J Xia*, Z Gao, H Lin, C Tan, SZ Li ECML 2022 - European Conference on Machine Learning, 2023 | 73* | 2023 |
| Temporal attention unit: Towards efficient spatiotemporal predictive learning C Tan, Z Gao, L Wu, S Li, Y Xu, SZ Li CVPR 2023 - IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022 | 70 | 2022 |
| Conditional Local Convolution for Spatio-temporal Meteorological Forecasting H Lin, Z Gao, Y Xu, L Wu, L Li, SZ Li AAAI 2022 - Association for the Advancement of Artificial Intelligence, 2022 | 67 | 2022 |
| A gan-based tunable image compression system L Wu, K Huang, H Shen WACV 2020 - IEEE/CVF Winter Conference on Applications of Computer Vision, 2021 | 64* | 2021 |
| DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding H Lin, Y Huang, M Liu, X Li, L Wu, S Ji, SZ Li arXiv preprint arXiv:2211.11214, 2022 | 60 | 2022 |
| Simvp: Towards simple yet powerful spatiotemporal predictive learning C Tan, Z Gao, S Li, SZ Li CVPR 2022 - IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022 | 58 | 2022 |
| ProteinInvBench: Benchmarking Protein Inverse Folding on Diverse Tasks, Models, and Metrics Z Gao, C Tan, Y Zhang, X Chen, L Wu, SZ Li NeurIPS 2023 - Advances in Neural Information Processing Systems, 2023 | 55* | 2023 |
| Multi-level disentanglement graph neural network L Wu, H Lin, J Xia, C Tan, SZ Li NCAA 2022 - Neural Computing and Applications, 2022 | 48* | 2022 |
| Knowledge Distillation Improves Graph Structure Augmentation for Graph Neural Networks L Wu, H Lin, Y Huang, SZ Li NeurIPS 2022 - Advances in Neural Information Processing Systems, 2022 | 45 | 2022 |
| Deep Clustering and Visualization for End-to-End High-Dimensional Data Analysis L Wu*, L Yuan*, G Zhao, H Lin, SZ Li TNNLS 2022 - IEEE Transactions on Neural Networks and Learning Systems, 2022 | 38* | 2022 |
| Openstl: A comprehensive benchmark of spatio-temporal predictive learning C Tan, S Li, Z Gao, W Guan, Z Wang, Z Liu, L Wu, SZ Li NeurIPS 2023 - Advances in Neural Information Processing Systems, 2024 | 37 | 2024 |
| Harnessing hard mixed samples with decoupled regularizer Z Liu, S Li, G Wang, L Wu, C Tan, SZ Li NeurIPS 2023 - Advances in Neural Information Processing Systems, 2023 | 31* | 2023 |
| Advances of Deep Learning in Protein Science: A Comprehensive Survey B Hu, C Tan, L Wu, J Zheng, J Xia, Z Gao, Z Liu, F Wu, G Zhang, SZ Li arXiv preprint arXiv:2403.05314, 2024 | 30* | 2024 |
| Quantifying the Knowledge in GNNs for Reliable Distillation into MLPs L Wu, H Lin, Y Huang, SZ Li ICML 2023 - International Conference on Machine Learning, 2023 | 25 | 2023 |
Stan Z. Li (李子青)Westlake University & CAS Institute of AutomationDirección de correo verificada de westlake.edu.cn
