代表性工作

[1]W. Tu, S. Zhou, X. Liu, X. Guo, Z. Cai, E. Zhu, and J. Cheng. Deep Fusion Clustering Network. Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021, pages: 9978-9987.[CCF Rank A]

[2]W. Tu, R. Guan, S. Zhou, C. Ma, X. Peng, Z. Cai, Z. Liu, J. Cheng, and X. Liu. Attribute-Missing Graph Clustering Network. Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024, pages: 15392-15401.[CCF Rank A]

[3]W. Tu, S. Zhou, X. Liu, Y. Liu, Z. Cai, E. Zhu, C. Zhang, and J. Cheng. Initializing Then Refining: A Simple Graph Attribute Imputation Network. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI), 2022,pages:3494-3500.[CCF Rank A]

[4]W. Tu, Q. Liao, S. Zhou, X. Peng, C. Ma, Z. Liu, X. Liu, Z. Cai, and K. He. RARE: Robust Masked Graph Autoencoder. IEEE Transactions on Knowledge and Data Engineering (IEEE T-KDE), 2023, (Early Access).[CCF Rank A, 影响因子：8.9]

[5]W. Tu, S. Zhou, X. Liu, C. Ge, Z. Cai, and Y. Liu. Hierarchically Contrastive Hard SampleMining for Graph Self-Supervised Pretraining. IEEE Transactions on Neural Networks andLearning Systems (IEEE T-NNLS), 2023,(Early Access).[中科院一区, 影响因子: 10.4]

[6]W. Tu, B. Xiao, X. Liu, S. Zhou, Z. Cai, and J. Chen. Revisiting Initializing Then Refining: An Incomplete and Missing Graph Imputation Network. IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS), 2024,(Early Access).[中科院一区,影响因子: 10.4]

[7]Y.Liu*,W. Tu*, S. Zhou, X. Liu, L. Song, X. Yang, and E. Zhu. Deep Graph Clustering via Dual Correlation Reduction. Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), 2022, pages: 9978-9987.[共同一作，CCF Rank A]

[8]L. Gong*,W. Tu*, S. Zhou, L. Zhao, Z. Liu, and X. Liu. Deep Fusion Clustering Network with Reliable Structure Preservation. IEEE Transactions on Neural Networks and Learning Systems (IEEE T-NNLS),35(6):7792-7803, 2024.[共同一作，中科院一区, 影响因子: 10.4]

[9]Fangqiang Xu,Wenxuan Tu^#, Fan Feng, Malitha Gunawardhana, Jiayuan Yang, Yun Gu, and Jichao Zhao. Dynamic Position Transformation and Boundary Refinement Network for Left Atrial Segmentation. Proceedings of the Twenty-Seventh International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2024.[通讯作者，CCF RankB]

[10]B. Jiang,W. Tu, C. Yang, and J. Yuan. Context-Integrated and Feature-Refined Network for Lightweight Object Parsing. IEEE Transactions on Image Processing (IEEE T-IP), 29: 5079-5093, 2020.[CCF Rank A,影响因子: 10.6]

[11]X. Tang,W. Tu, K. Li, and J. Cheng. DFFNet: An IoT-Perceptive dual Feature Fusion Network for General Real-Time Semantic Segmentation. Information Sciences, 565: 326-343, 2021.[中科院一区, 影响因子: 8.1]

[12]M.Liu,W.Tu, K.Liang, and X.Liu. Structural Embedding Pre-Training for Deep Temporal Graph Learning. Proceedings of the Fifth China Symposium on Cognitive Computing and Hybrid Intelligence (CCHI), 2023.[CAA Rank A,最佳学生论文]

[13]L.Song,W.Tu, S.Zhou, and E.Zhu. GANN: Graph Alignment Neural Network for Semi-Supervised Learning. Pattern Recognition,154: 110484,2024.[中科院一区, 影响因子: 8.1]

[14]R.Guan, Z.Li,W.Tu, J.Wang, Y.Liu, X.Li, C.Tang, and R.Feng. Contrastive Multi-view Subspace Clustering of Hyperspectral Images based on Graph Convolutional Networks. IEEE Transactions on Geoscience and Remote Sensing (IEEET-GRS), 62: 1-14,2024.[中科院一区, 影响因子: 8.2]

[15]L.Gong, S.Zhou,W.Tu, and X.Liu. Attributed Graph Clustering with Dual Redundancy Reduction. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence (IJCAI), 2022, pages: 3015-3021.[CCF Rank A]