1．Yujie Mo, Heng Tao Shen, Xiaofeng Zhu:Unsupervised multi-view graph representation learning with dual weight-net. Inf. Fusion 114: 102669 (2025)

2．Yujie Mo, Heng Tao Shen, Xiaofeng Zhu: Efficient self-supervised heterogeneous graph representation learning with reconstruction. Inf. Fusion 117: 102846 (2025)

3．Liang Peng, Songyue Cai, Zongqian Wu, Huifang Shang, Xiaofeng Zhu, Xiaoxiao Li: MMGPL: Multimodal Medical Data Analysis with Graph Prompt Learning. Medical Image Anal. 97: 103225 (2024)

4．Jiangzhang Gan, Rongyao Hu, Yujie Mo, Zhao Kang, Liang Peng, Yonghua Zhu, Xiaofeng Zhu: Multigraph Fusion for Dynamic Graph Convolutional Network. IEEE Trans. Neural Networks Learn. Syst. 35(1): 196-207 (2024)

5．Liang Peng, Rongyao Hu, Fei Kong, Jiangzhang Gan, Yujie Mo, Xiaoshuang Shi, Xiaofeng Zhu:Reverse Graph Learning for Graph Neural Network. IEEE Trans. Neural Networks Learn. Syst. 35(4): 4530-4541 (2024)

6．Liang Peng, Yujie Mo, Jie Xu, Jialie Shen, Xiaoshuang Shi, Xiaoxiao Li, Heng Tao Shen, Xiaofeng Zhu:GRLC: Graph Representation Learning With Constraints. IEEE Trans. Neural Networks Learn. Syst. 35(6): 8609-8622 (2024)

7．Zongqian Wu, Yujie Mo, Peng Zhou, Shangbo Yuan, Xiaofeng Zhu:Self-Training Based Few-Shot Node Classification by Knowledge Distillation. AAAI 2024: 15988-15995

8．Jie Xu, Yazhou Ren, Xiaolong Wang, Lei Feng, Zheng Zhang, Gang Niu, Xiaofeng Zhu: Investigating and Mitigating the Side Effects of Noisy Views for Self-Supervised Clustering Algorithms in Practical Multi-View Scenarios. CVPR 2024: 22957-22966

9．Yujie Mo, Feiping Nie, Ping Hu, Heng Tao Shen, Zheng Zhang, Xinchao Wang, Xiaofeng Zhu: Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View. ICLR 2024

10．Jincheng Huang, Jialie Shen, Xiaoshuang Shi, Xiaofeng Zhu: On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective. ICML 2024

11．Mengmeng Zhan, Zongqian Wu, Rongyao Hu, Ping Hu, Heng Tao Shen, Xiaofeng Zhu:Towards Dynamic-Prompting Collaboration for Source-Free Domain Adaptation. IJCAI 2024: 1643-1651

12．Jincheng Huang, Yujie Mo, Ping Hu, Xiaoshuang Shi, Shangbo Yuan, Zeyu Zhang, Xiaofeng Zhu:Exploring the Role of Node Diversity in Directed Graph Representation Learning. IJCAI 2024: 2072-2080

13．Yudi Huang, Yujie Mo, Yujing Liu, Ci Nie, Guoqiu Wen, Xiaofeng Zhu:Multiplex Graph Representation Learning via Bi-level Optimization. IJCAI 2024: 2081-2089

14．Caixuan Luo, Jie Xu, Yazhou Ren, Junbo Ma, Xiaofeng Zhu:Simple Contrastive Multi-View Clustering with Data-Level Fusion. IJCAI 2024: 4697-4705

15．Zongqian Wu, Yujing Liu, Mengmeng Zhan, Ping Hu, Xiaofeng Zhu: Adaptive Multi-Modality Prompt Learning. ACM Multimedia 2024: 8672-8680

16．Yujie Mo, Zhihe Lu, Runpeng Yu, Xiaofeng Zhu, Xinchao Wang: Revisiting Self-Supervised Heterogeneous Graph Learning from Spectral Clustering Perspective. NeurIPS 2024

17．Jie Xu, Yazhou Ren, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu: UNTIE: Clustering analysis with disentanglement in multi-view information fusion. Inf. Fusion 100: 101937 (2023)

18．Hangchen Xiang, Junyi Shen, Qingguo Yan, Meilian Xu, Xiaoshuang Shi, Xiaofeng Zhu:Multi-scale representation attention based deep multiple instance learning for gigapixel whole slide image analysis. Medical Image Anal. 89: 102890 (2023)

19．Guolin Zhang, Zehui Hu, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu: Dynamic graph convolutional networks by semi-supervised contrastive learning. Pattern Recognit. 139: 109486 (2023)

20．Jie Xu, Chao Li, Liang Peng, Yazhou Ren, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu: Adaptive Feature Projection With Distribution Alignment for Deep Incomplete Multi-View Clustering. IEEE Trans. Image Process. 32: 1354-1366 (2023)

21．Yujie Mo, Yuhuan Chen, Yajie Lei, Liang Peng, Xiaoshuang Shi, Changan Yuan, Xiaofeng Zhu:Multiplex Graph Representation Learning Via Dual Correlation Reduction. IEEE Trans. Knowl. Data Eng. 35(12): 12814-12827 (2023)

22．Liang Peng, Nan Wang, Jie Xu, Xiaofeng Zhu, Xiaoxiao Li:GATE: Graph CCA for Temporal Self-Supervised Learning for Label-Efficient fMRI Analysis. IEEE Trans. Medical Imaging 42(2): 391-402 (2023)

23．Liang Peng, Nan Wang, Nicha C. Dvornek, Xiaofeng Zhu, Xiaoxiao Li:FedNI: Federated Graph Learning With Network Inpainting for Population-Based Disease Prediction. IEEE Trans. Medical Imaging 42(7): 2032-2043 (2023)

24．Yujie Mo, Zongqian Wu, Yuhuan Chen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu: Multiplex Graph Representation Learning via Common and Private Information Mining. AAAI 2023: 9217-9225

25．Yujie Mo, Yajie Lei, Jialie Shen, Xiaoshuang Shi, Heng Tao Shen, Xiaofeng Zhu:Disentangled Multiplex Graph Representation Learning. ICML 2023: 24983-25005

26．Peng Zhou, Zongqian Wu, Xiangxiang Zeng, Guoqiu Wen, Junbo Ma, Xiaofeng Zhu: Totally Dynamic Hypergraph Neural Networks. IJCAI 2023: 2476-2483

27．Xuan Chen, Weiheng Fu, Tian Li, Xiaoshuang Shi, Hengtao Shen, Xiaofeng Zhu:Co-assistant Networks for Label Correction. MICCAI (3) 2023: 159-168

28．Liang Peng, Xin Wang, Xiaofeng Zhu:Unsupervised Multiplex Graph learning with Complementary and Consistent Information. ACM Multimedia 2023: 454-462

29．Yujing Liu, Zongqian Wu, Zhengyu Lu, Guoqiu Wen, Junbo Ma, Guangquan Lu, Xiaofeng Zhu:Multi-teacher Self-training for Semi-supervised Node Classification with Noisy Labels. ACM Multimedia 2023: 2946-2954

30．Jie Xu, Shuo Chen, Yazhou Ren, Xiaoshuang Shi, Hengtao Shen, Gang Niu, Xiaofeng Zhu: Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration. NeurIPS 2023

31．Yonghua Zhu, Junbo Ma, Changan Yuan, Xiaofeng Zhu:Interpretable learning based Dynamic Graph Convolutional Networks for Alzheimer's Disease analysis. Inf. Fusion 77: 53-61 (2022)

32．Xiaofeng Zhu, Shichao Zhang, Yonghua Zhu, Pengfei Zhu, Yue Gao: Unsupervised Spectral Feature Selection With Dynamic Hyper-Graph Learning. IEEE Trans. Knowl. Data Eng. 34(6): 3016-3028 (2022)

33．Yujie Mo, Liang Peng, Jie Xu, Xiaoshuang Shi, Xiaofeng Zhu: Simple Unsupervised Graph Representation Learning. AAAI 2022: 7797-7805

34．Jie Xu, Chao Li, Yazhou Ren, Liang Peng, Yujie Mo, Xiaoshuang Shi, Xiaofeng Zhu:Deep Incomplete Multi-View Clustering via Mining Cluster Complementarity. AAAI 2022: 8761-8769

35．Jie Xu, Huayi Tang, Yazhou Ren, Liang Peng, Xiaofeng Zhu, Lifang He:Multi-level Feature Learning for Contrastive Multi-view Clustering. CVPR 2022: 16030-16039

36．Jiangzhang Gan, Rongyao Hu, Mengmeng Zhan, Yujie Mo, Yingying Wan, Xiaofeng Zhu:Multi-view Unsupervised Graph Representation Learning. IJCAI 2022: 2987-2993

37．Zongqian Wu, Peng Zhou, Guoqiu Wen, Yingying Wan, Junbo Ma, Debo Cheng, Xiaofeng Zhu:Information Augmentation for Few-shot Node Classification. IJCAI 2022: 3601-3607

38．Tingsong Xiao, Lu Zeng, Xiaoshuang Shi, Xiaofeng Zhu, Guorong Wu:Dual-Graph Learning Convolutional Networks for Interpretable Alzheimer's Disease Diagnosis. MICCAI (8) 2022: 406-415

39．Yujie Mo, Yuhuan Chen, Liang Peng, Xiaoshuang Shi, Xiaofeng Zhu:Simple Self-supervised Multiplex Graph Representation Learning. ACM Multimedia 2022: 3301-3309

40．Rongyao Hu, Liang Peng, Jiangzhang Gan, Xiaoshuang Shi, Xiaofeng Zhu:Complementary Graph Representation Learning for Functional Neuroimaging Identification. ACM Multimedia 2022: 3385-3393

41．Heng Tao Shen, Xiaofeng Zhu, Zheng Zhang, Shui-Hua Wang, Yi Chen, Xing Xu, Jie Shao:Heterogeneous data fusion for predicting mild cognitive impairment conversion. Inf. Fusion 66: 54-63 (2021)

42．Xiaofeng Zhu, Hongming Li, Heng Tao Shen, Zheng Zhang, Yanli Ji, Yong Fan:Fusing functional connectivity with network nodal information for sparse network pattern learning of functional brain networks. Inf. Fusion 75: 131-139 (2021)

43．Chang-An Yuan, Zhi Zhong, Cong Lei, Xiaofeng Zhu, Rongyao Hu:Adaptive reverse graph learning for robust subspace learning. Inf. Process. Manag. 58(6): 102733 (2021)

44．Xiaofeng Zhu, Bin Song, Feng Shi, Yanbo Chen, Rongyao Hu, Jiangzhang Gan, Wenhai Zhang, Man Li, Liye Wang, Yaozong Gao, Fei Shan, Dinggang Shen:Joint prediction and time estimation of COVID-19 developing severe symptoms using chest CT scan. Medical Image Anal. 67: 101824 (2021)

45．Yingying Zhu, Minjeong Kim, Xiaofeng Zhu, Daniel Kaufer, Guorong Wu:Long range early diagnosis of Alzheimer's disease using longitudinal MR imaging data. Medical Image Anal. 67: 101825 (2021)

46．Jiangzhang Gan, Zi-Wen Peng, Xiaofeng Zhu, Rongyao Hu, Junbo Ma, Guorong Wu:Brain functional connectivity analysis based on multi-graph fusion. Medical Image Anal. 71: 102057 (2021)

47．Xiaofeng Zhu, Jianye Yang, Chengyuan Zhang, Shichao Zhang:Efficient Utilization of Missing Data in Cost-Sensitive Learning. IEEE Trans. Knowl. Data Eng. 33(6): 2425-2436 (2021)

48．Rongyao Hu, Zi-Wen Peng, Xiaofeng Zhu, Jiangzhang Gan, Yonghua Zhu, Junbo Ma, Guorong Wu:Multi-Band Brain Network Analysis for Functional Neuroimaging Biomarker Identification. IEEE Trans. Medical Imaging 40(12): 3843-3855 (2021)

49．Heng Tao Shen, Yonghua Zhu, Wei Zheng, Xiaofeng Zhu:Half-Quadratic Minimization for Unsupervised Feature Selection on Incomplete Data. IEEE Trans. Neural Networks Learn. Syst. 32(7): 3122-3135 (2021)

50．Rongyao Hu, Zhenyun Deng, Xiaofeng Zhu:Multi-scale Graph Fusion for Co-saliency Detection. AAAI 2021: 7789-7796

51．Jie Xu, Yazhou Ren, Huayi Tang, Xiaorong Pu, Xiaofeng Zhu, Ming Zeng, Lifang He:Multi-VAE: Learning Disentangled View-common and View-peculiar Visual Representations for Multi-view Clustering. ICCV 2021: 9214-9223

52．Xiaofeng Zhu, Yonghua Zhu, Wei Zheng:Spectral rotation for deep one-step clustering. Pattern Recognit. 105: 107175 (2020)

53．Xiaofeng Zhu, Shichao Zhang, Jilian Zhang, Yonggang Li, Guangquan Lu, Yang Yang: Sparse Graph Connectivity for Image Segmentation. ACM Trans. Knowl. Discov. Data 14(4): 46:1-46:19 (2020)

54．Xiaofeng Zhu, Shichao Zhang, Yonghua Zhu, Wei Zheng, Yang Yang:Self-weighted Multi-view Fuzzy Clustering. ACM Trans. Knowl. Discov. Data 14(4): 48:1-48:17 (2020)

55．Jiangzhang Gan, Xiaofeng Zhu, Rongyao Hu, Yonghua Zhu, Junbo Ma, Zi-Wen Peng, Guorong Wu: Multi-graph Fusion for Functional Neuroimaging Biomarker Detection. IJCAI 2020: 580-586

56．Junbo Ma, Xiaofeng Zhu, Defu Yang, Jiazhou Chen, Guorong Wu:Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer's Disease Analysis. MICCAI (7) 2020: 387-396

57．Xiaofeng Zhu, Shichao Zhang, Yonggang Li, Jilian Zhang, Lifeng Yang, Yue Fang: Low-Rank Sparse Subspace for Spectral Clustering. IEEE Trans. Knowl. Data Eng. 31(8): 1532-1543 (2019)

58．Xiaofeng Zhu, Shichao Zhang, Wei He, Rongyao Hu, Cong Lei, Pengfei Zhu:One-Step Multi-View Spectral Clustering. IEEE Trans. Knowl. Data Eng. 31(10): 2022-2034 (2019)

59．Xiaofeng Zhu: Prediction of Mild Cognitive Impairment Conversion Using Auxiliary Information. IJCAI 2019: 4475-4481

60．Xiaofeng Zhu, Dinggang Shen:Robust and Discriminative Brain Genome Association Study. MICCAI (4) 2019: 456-464

61．Xiaofeng Zhu, Shichao Zhang, Rongyao Hu, Yonghua Zhu, Jingkuan Song:Local and Global Structure Preservation for Robust Unsupervised Spectral Feature Selection. IEEE Trans. Knowl. Data Eng. 30(3): 517-529 (2018)

62．Shichao Zhang, Xuelong Li, Ming Zong, Xiaofeng Zhu, Ruili Wang:Efficient kNN Classification With Different Numbers of Nearest Neighbors. IEEE Trans. Neural Networks Learn. Syst. 29(5): 1774-1785 (2018)

63．Xiaofeng Zhu, Hongming Li, Yong Fan: Parameter-Free Centralized Multi-Task Learning for Characterizing Developmental Sex Differences in Resting State Functional Connectivity. AAAI 2018: 2660-2668

64．Wei Zheng, Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang:Robust Feature Selection on Incomplete Data. IJCAI 2018: 3191-3197

65．Xiaofeng Zhu, Cong Lei, Hao Yu, Yonggang Li, Jiangzhang Gan, Shichao Zhang:Robust Graph Dimensionality Reduction. IJCAI 2018: 3257-3263

66．Yonghua Zhu, Xiaofeng Zhu, Wei Zheng:Robust Multi-view Learning via Half-quadratic Minimization. IJCAI 2018: 3278-3284

67．Xiaofeng Zhu, Heung-Il Suk, Li Wang, Seong-Whan Lee, Dinggang Shen:A novel relational regularization feature selection method for joint regression and classification in AD diagnosis. Medical Image Anal. 38: 205-214 (2017)

68．Xiaofeng Zhu, Heung-Il Suk, Heng Huang, Dinggang Shen:Low-Rank Graph-Regularized Structured Sparse Regression for Identifying Genetic Biomarkers. IEEE Trans. Big Data 3(4): 405-414 (2017)

69．Shichao Zhang, Xuelong Li, Ming Zong, Xiaofeng Zhu, Debo Cheng:Learning k for kNN Classification. ACM Trans. Intell. Syst. Technol. 8(3): 43:1-43:19 (2017)

70．Xiaofeng Zhu, Xuelong Li, Shichao Zhang, Zongben Xu, Litao Yu, Can Wang:Graph PCA Hashing for Similarity Search. IEEE Trans. Multim. 19(9): 2033-2044 (2017)

71．Xiaofeng Zhu, Xuelong Li, Shichao Zhang, Chunhua Ju, Xindong Wu:Robust Joint Graph Sparse Coding for Unsupervised Spectral Feature Selection. IEEE Trans. Neural Networks Learn. Syst. 28(6): 1263-1275 (2017)

72．Xiaofeng Zhu, Wei He, Yonggang Li, Yang Yang, Shichao Zhang, Rongyao Hu, Yonghua Zhu:One-Step Spectral Clustering via Dynamically Learning Affinity Matrix and Subspace. AAAI 2017: 2963-2969

73．Xiaofeng Zhu, Yonghua Zhu, Shichao Zhang, Rongyao Hu, Wei He:Adaptive Hypergraph Learning for Unsupervised Feature Selection. IJCAI 2017: 3581-3587

74．Xiaofeng Zhu, Kim-Han Thung, Ehsan Adeli, Yu Zhang, Dinggang Shen:Maximum Mean Discrepancy Based Multiple Kernel Learning for Incomplete Multimodality Neuroimaging Data. MICCAI (3) 2017: 72-80

75．Xiaofeng Zhu, Heung-Il Suk, Seong-Whan Lee, Dinggang Shen:Subspace Regularized Sparse Multitask Learning for Multiclass Neurodegenerative Disease Identification. IEEE Trans. Biomed. Eng. 63(3): 607-618 (2016)

76．Xiaofeng Zhu, Xuelong Li, Shichao Zhang:Block-Row Sparse Multiview Multilabel Learning for Image Classification. IEEE Trans. Cybern. 46(2): 450-461 (2016)