| Scalable multi-view subspace clustering with unified anchors M Sun, P Zhang, S Wang, S Zhou, W Tu, X Liu, E Zhu, C Wang Proceedings of the 29th ACM International Conference on Multimedia, 3528-3536, 2021 | 132 | 2021 |
| Deep graph clustering via dual correlation reduction Y Liu, W Tu, S Zhou, X Liu, L Song, X Yang, E Zhu Proceedings of the AAAI conference on artificial intelligence 36 (7), 7603-7611, 2022 | 131 | 2022 |
| Deep fusion clustering network W Tu, S Zhou, X Liu, X Guo, Z Cai, E Zhu, J Cheng Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9978-9987, 2021 | 112 | 2021 |
| One pass late fusion multi-view clustering X Liu, L Liu, Q Liao, S Wang, Y Zhang, W Tu, C Tang, J Liu, E Zhu International conference on machine learning, 6850-6859, 2021 | 89 | 2021 |
| Highly-efficient incomplete large-scale multi-view clustering with consensus bipartite graph S Wang, X Liu, L Liu, W Tu, X Zhu, J Liu, S Zhou, E Zhu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 80 | 2022 |
| Simple contrastive graph clustering Y Liu, X Yang, S Zhou, X Liu, S Wang, K Liang, W Tu, L Li IEEE Transactions on Neural Networks and Learning Systems, 2023 | 75 | 2023 |
| Reasoning over different types of knowledge graphs: Static, temporal and multi-modal K Liang, L Meng, M Liu, Y Liu, W Tu, S Wang, S Zhou, X Liu, F Sun arXiv preprint arXiv:2212.05767, 7576-7584, 2022 | 63 | 2022 |
| Hard sample aware network for contrastive deep graph clustering Y Liu, X Yang, S Zhou, X Liu, Z Wang, K Liang, W Tu, L Li, J Duan, ... Proceedings of the AAAI conference on artificial intelligence 37 (7), 8914-8922, 2023 | 60 | 2023 |
| Self-representation subspace clustering for incomplete multi-view data J Liu, X Liu, Y Zhang, P Zhang, W Tu, S Wang, S Zhou, W Liang, S Wang, ... Proceedings of the 29th ACM international conference on multimedia, 2726-2734, 2021 | 57 | 2021 |
| Cluster-guided contrastive graph clustering network X Yang, Y Liu, S Zhou, S Wang, W Tu, Q Zheng, X Liu, L Fang, E Zhu Proceedings of the AAAI conference on artificial intelligence 37 (9), 10834 …, 2023 | 44 | 2023 |
| Knowledge graph contrastive learning based on relation-symmetrical structure K Liang, Y Liu, S Zhou, W Tu, Y Wen, X Yang, X Dong, X Liu IEEE Transactions on Knowledge and Data Engineering, 2023 | 42 | 2023 |
| An improved method for the fitting and prediction of the number of covid-19 confirmed cases based on lstm B Yan, X Tang, B Liu, J Wang, Y Zhou, G Zheng, Q Zou, Y Lu, W Tu arXiv preprint arXiv:2005.03446, 2020 | 42 | 2020 |
| DFFNet: An IoT-perceptive dual feature fusion network for general real-time semantic segmentation X Tang, W Tu, K Li, J Cheng Information Sciences 565, 326-343, 2021 | 37 | 2021 |
| Learn from relational correlations and periodic events for temporal knowledge graph reasoning K Liang, L Meng, M Liu, Y Liu, W Tu, S Wang, S Zhou, X Liu Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 32 | 2023 |
| Attributed Graph Clustering with Dual Redundancy Reduction. L Gong, S Zhou, W Tu, X Liu IJCAI, 3015-3021, 2022 | 31 | 2022 |
| Align then fusion: Generalized large-scale multi-view clustering with anchor matching correspondences S Wang, X Liu, S Liu, J Jin, W Tu, X Zhu, E Zhu Advances in Neural Information Processing Systems 35, 5882-5895, 2022 | 27 | 2022 |
| Initializing Then Refining: A Simple Graph Attribute Imputation Network. W Tu, S Zhou, X Liu, Y Liu, Z Cai, E Zhu, C Zhang, J Cheng IJCAI, 3494-3500, 2022 | 23 | 2022 |
| Self-supervised temporal graph learning with temporal and structural intensity alignment M Liu, K Liang, Y Zhao, W Tu, S Zhou, X Gan, X Liu, K He IEEE Transactions on Neural Networks and Learning Systems, 2024 | 22 | 2024 |
| scDFC: A deep fusion clustering method for single-cell RNA-seq data D Hu, K Liang, S Zhou, W Tu, M Liu, X Liu Briefings in Bioinformatics 24 (4), bbad216, 2023 | 20 | 2023 |
| Improved dual correlation reduction network Y Liu, S Zhou, X Liu, W Tu, X Yang arXiv preprint arXiv:2202.12533, 2022 | 20 | 2022 |
