| SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation J Xia, L Wu, J Chen, B Hu, SZ Li WWW 2022, 0 | 176* | |
| Co-learning: Learning from noisy labels with self-supervision C Tan, J Xia, L Wu, SZ Li ACM MM 2021, 2021 | 93 | 2021 |
| ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning J Xia, L Wu, J Chen, G Wang, SZ Li ICML 2022, 2022 | 92 | 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 PKDD 2022, 2023 | 58* | 2023 |
| Mole-BERT: Rethinking Pre-training Graph Neural Networks for Molecules J Xia, C Zhao, B Hu, Z Gao, C Tan, Y Liu, S Li, SZ Li ICLR 2023, 2023 | 49 | 2023 |
| A Systematic Survey of Chemical Pre-trained Models J Xia, Y Zhu, Y Du, SZ Li IJCAI 2023, 2022 | 38* | 2022 |
| Temporal attention unit: Towards efficient spatiotemporal predictive learning C Tan, Z Gao, S Li, Y Xu, J Xia, LI Siyuan, SZ Li CVPR 2023, 2022 | 38 | 2022 |
| A survey of pretraining on graphs: Taxonomy, methods, and applications J Xia, Y Zhu, Y Du, SZ Li arXiv preprint arXiv:2202.07893, 2022 | 37 | 2022 |
| Generative de novo protein design with global context C Tan, Z Gao, J Xia, B Hu, SZ Li arXiv preprint arXiv:2204.10673, 2022 | 34 | 2022 |
| A Survey of Deep Graph Clustering: Taxonomy, Challenge, Application, and Open Resource Y Liu, J Xia, S Zhou, X Yang, K Liang, C Fan, Y Zhuang, SZ Li, X Liu, K He arXiv preprint arXiv:2211.12875, 2022 | 32 | 2022 |
| CVT-SLR: Contrastive Visual-Textual Transformation for Sign Language Recognition with Variational Alignment J Zheng, Y Wang, C Tan, S Li, G Wang, J Xia, Y Chen, SZ Li CVPR 2023, 2023 | 25 | 2023 |
| Dink-net: Neural clustering on large graphs Y Liu, K Liang, J Xia, S Zhou, X Yang, X Liu, SZ Li ICML 2023, 2023 | 22 | 2023 |
| Protein language models and structure prediction: Connection and progression B Hu, J Xia, J Zheng, C Tan, Y Huang, Y Xu, SZ Li arXiv preprint arXiv:2211.16742, 2022 | 19 | 2022 |
| Towards effective and generalizable fine-tuning for pre-trained molecular graph models J Xia, J Zheng, C Tan, G Wang, SZ Li bioRxiv, 2022.02. 03.479055, 2022 | 16 | 2022 |
| A Survey of Deep Graph Clustering: Taxonomy Y Liu, J Xia, S Zhou, S Wang, X Guo, X Yang, K Liang, W Tu, ZS Li, X Liu Challenge, and Application, 2022 | 16 | 2022 |
| Using Context-to-Vector with Graph Retrofitting to Improve Word Embeddings J Zheng, Y Wang, G Wang, J Xia, Y Huang, G Zhao, Y Zhang, S Li ACL 2022 1, 8154-8163, 2022 | 13 | 2022 |
| Convert: Contrastive graph clustering with reliable augmentation X Yang, C Tan, Y Liu, K Liang, S Wang, S Zhou, J Xia, SZ Li, X Liu, E Zhu Proceedings of the 31st ACM International Conference on Multimedia, 319-327, 2023 | 11 | 2023 |
| GNN Cleaner: Label Cleaner for Graph Structured Data J Xia, H Lin, Y Xu, C Tan, L Wu, S Li, SZ Li TKDE 2023, 2023 | 11* | 2023 |
| CoSP: Co-supervised pretraining of pocket and ligand Z Gao, C Tan, J Xia, SZ Li ECML-PKDD 2023, 2022 | 11 | 2022 |
| Multi-level disentanglement graph neural network L Wu, H Lin, J Xia, C Tan, SZ Li Neural Computing and Applications 34 (11), 9087-9101, 2022 | 10 | 2022 |
Stan Z. Li (李子青)Westlake University & CAS Institute of Automation在 westlake.edu.cn 的电子邮件经过验证
