Papers

  1. Xiaoxiao Ma*, FanzhenLiu*, Jia Wu, Jian Yang, Shan Xue, Quan Z. Sheng, Rethinking Unsupervised Graph Anomaly Detection with Deep Learning: Residuals and Objectives, IEEE Transactions on Knowledge and Data Engineering (TKDE), 37(2): 881-895, 2025.
  2. Xiaoxiao Ma, Ruikun Li, Fanzhen Liu, Kaize Ding, Jian Yang, Jia Wu, Graph Anomaly Detection with Few Labels: A Data-Centric Approach, Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’24), Barcelona, Spain, 2024.
  3. Fanzhen Liu*, Xiaoxiao Ma*, Jia Wu, Jian Yang, Shan Xue, Amin Beheshti, Chuan Zhou, Hao Peng, Quan Z. Sheng, Charu C. Aggarwal, DAGAD: Data Augmentation for Graph Anomaly Detection, regular paper, Proceedings of the 22nd IEEE International Conference on Data Mining (ICDM’22), Orlando, USA, 2022. [Code]
  4. Fanzhen Liu, Zhao Li, Baokun Wang, Jia Wu, Jian Yang, Jiaming Huang, Yiqing Zhang, Weiqiang Wang, Shan Xue, Surya Nepal, Quan Z. Sheng, eRiskCom: An E-commerce Risky Community Detection Platform, The VLDB Journal, 31:1085-1101, 2022.
  5. Xing Su, Shan Xue, Fanzhen Liu, Jia Wu, Jian Yang, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Di Jin, Quan Z. Sheng, Philip S. Yu, A Comprehensive Survey on Community Detection with Deep Learning, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 1-21, 2022, early access. Highly Cited Paper. [GitHub repository][Supplementary Materials]
  6. Fanzhen Liu, Shan Xue, Jia Wu, Chuan Zhou, Wenbin Hu, Cecile Paris, Surya Nepal, Jian Yang, Philip S. Yu, Deep Learning for Community Detection: Progress, Challenges and Opportunities, Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI’20), Survey Track, Yokohama, Japan, 2021. Most Influential IJCAI Paper, Ranked 1st in 2020. [GitHub repository]
  7. Fanzhen Liu, Jia Wu, Shan Xue, Chuan Zhou, Jian Yang, Quanzheng Sheng, Detecting the Evolving Community Structure in Dynamic Social Networks, World Wide Web Journal, 23:715–733, 2020. [Code]
  8. Sanmin Liu, Shan Xue, Fanzhen Liu, Jieren Cheng, Xiulai Li, Chao Kong, Jia Wu, Microcluster-Based Incremental Ensemble Learning for Noisy, Nonstationary Data Streams, Complexity, 2020.
  9. Fanzhen Liu, Jia Wu, Chuan Zhou, Jian Yang, Evolutionary Community Detection in Dynamic Social Networks, Proceedings of the 29th International Joint Conference on Neural Networks (IJCNN’19), Budapest, Hungary, 2019. [Code]
  10. Zhen Su, Fanzhen Liu, Chao Gao, Shupeng Gao, Xianghua Li, Inferring Infection Rate Based on Observations in Complex Networks, Chaos, Solitons & Fractals, 107:170-176, 2018.
  11. Fanzhen Liu, Zhengpeng Chen, Yali Cui, Chen Liu, Xianghua Li, Chao Gao, A Hybrid Evolutionary Algorithm for Community Detection, Proceedings of the 16th International Conference on Web Intelligence (WI’17), Leipzig, Germany, 2017.
  12. Fanzhen Liu, Jiaqi Zhong, Chen Liu, Chao Gao, Xianghua Li, A Novel Strategy of Initializing the Population Size for Ant Colony Optimization Algorithms in TSP, Proceedings of the 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD’17), Guilin, China, 2017.
  13. Zhengpeng Chen*, Fanzhen Liu*, Chao Gao, Xianghua Li, Zili Zhang, An Enhanced Particle Swarm Optimization Based on Physarum Model for Community Detection, Proceedings of the 8th International Conference on Swarm Intelligence (ICSI’17), Fukuoka, Japan, 2017.
  14. Mingxin Liang*, Fanzhen Liu*, Chao Gao, Zili Zhang, Robustness Analysis of the Complex Network, Proceedings of the 6th Data Driven Control and Learning Systems Conference (DDCLS’17), Chongqing, China, 2017.
* indicates equal contribution.