| A comprehensive survey on community detection with deep learning X Su, S Xue, F Liu, J Wu, J Yang, C Zhou, W Hu, C Paris, S Nepal, D Jin, ... IEEE Transactions on Neural Networks and Learning Systems, 2022 | 442 | 2022 |
| Deep Learning for Community Detection: Progress, Challenges and Opportunities F Liu, S Xue, J Wu, C Zhou, W Hu, C Paris, S Nepal, J Yang, PS Yu International Joint Conference on Artificial Intelligence, IJCAI-20, 4981-4987, 2020 | 300 | 2020 |
| Detecting the evolving community structure in dynamic social networks F Liu, J Wu, S Xue, C Zhou, J Yang, Q Sheng World Wide Web 23, 715-733, 2020 | 72 | 2020 |
| DAGAD: Data augmentation for graph anomaly detection F Liu, X Ma, J Wu, J Yang, S Xue, A Beheshti, C Zhou, H Peng, QZ Sheng, ... 2022 IEEE international conference on data mining (ICDM), 259-268, 2022 | 52 | 2022 |
| Evolutionary community detection in dynamic social networks F Liu, J Wu, C Zhou, J Yang 2019 International Joint Conference on Neural Networks (IJCNN), 1-7, 2019 | 35 | 2019 |
| eRiskCom: an e-commerce risky community detection platform F Liu, Z Li, B Wang, J Wu, J Yang, J Huang, Y Zhang, W Wang, S Xue, ... The VLDB Journal 31 (5), 1085-1101, 2022 | 16 | 2022 |
| A novel strategy of initializing the population size for ant colony optimization algorithms in TSP F Liu, J Zhong, C Liu, C Gao, X Li 2017 13th International Conference on Natural Computation, Fuzzy Systems and …, 2017 | 8 | 2017 |
| Graph anomaly detection with few labels: A data-centric approach X Ma, R Li, F Liu, K Ding, J Yang, J Wu Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 6 | 2024 |
| Robustness analysis of the complex network M Liang, F Liu, C Gao, Z Zhang 2017 6th Data Driven Control and Learning Systems (DDCLS), 638-643, 2017 | 6 | 2017 |
| Inferring infection rate based on observations in complex networks Z Su, F Liu, C Gao, S Gao, X Li Chaos, Solitons & Fractals 107, 170-176, 2018 | 4 | 2018 |
| An Enhanced Particle Swarm Optimization Based on Physarum Model for Community Detection Z Chen, F Liu, C Gao, X Li, Z Zhang Advances in Swarm Intelligence: 8th International Conference, ICSI 2017 …, 2017 | 4 | 2017 |
| Microcluster‐Based Incremental Ensemble Learning for Noisy, Nonstationary Data Streams S Liu, S Xue, F Liu, J Cheng, X Li, C Kong, J Wu Complexity 2020 (1), 6147378, 2020 | 3 | 2020 |
| A hybrid evolutionary algorithm for community detection F Liu, Z Chen, Y Cui, C Liu, X Li, C Gao Proceedings of the International Conference on Web Intelligence, 469-475, 2017 | 3 | 2017 |
| New recipes for graph anomaly detection: Forward diffusion dynamics and graph generation X Ma, R Li, F Liu, K Ding, J Yang, J Wu | 1 | |
| Rethinking Unsupervised Graph Anomaly Detection with Deep Learning: Residuals and Objectives X Ma, F Liu, J Wu, J Yang, S Xue, QZ Sheng IEEE Transactions on Knowledge and Data Engineering, 2024 | | 2024 |
| Dynamic community detection via evolutionary clustering F Liu Macquarie University, 2019 | | 2019 |
Jia WuAssociate Professor, School of Computing, Macquarie University, Sydney, AustraliaAdresse e-mail validée de mq.edu.au