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 Sample Mining for Graph Self-Supervised Pretraining. IEEE Transactions on Neural Networks and Learning 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 Rank B]

[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, 最佳员工论文]

[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 (IEEE T-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]