| Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection Y Liu, X Ao, Z Qin, J Chi, J Feng, H Yang, Q He Proceedings of the Web Conference 2021, 3168-3177, 2021 | 357 | 2021 |
| Intelligent financial fraud detection practices in post-pandemic era X Zhu, X Ao, Z Qin, Y Chang, Y Liu, Q He, J Li The Innovation 2 (4), 2021 | 178 | 2021 |
| Financial Defaulter Detection on Online Credit Payment via Multi-view Attributed Heterogeneous Information Network Q Zhong, Y Liu, X Ao, B Hu, J Feng, J Tang, Q He Proceedings of The Web Conference 2020, 785-795, 2020 | 126 | 2020 |
| AUC-oriented Graph Neural Network for Fraud Detection M Huang, Y Liu, X Ao, K Li, J Chi, J Feng, H Yang, Q He Proceedings of the ACM Web Conference 2022, 1311-1321, 2022 | 90 | 2022 |
| Grid-based DBSCAN: Indexing and inference T Boonchoo, X Ao, Y Liu, W Zhao, F Zhuang, Q He Pattern Recognition 90, 271-284, 2019 | 71 | 2019 |
| Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN K Li, Y Liu, X Ao, J Chi, J Feng, H Yang, Q He Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 69 | 2022 |
| FLOOD: A Flexible Invariant Learning Framework for Out-of-Distribution Generalization on Graphs Y Liu, X Ao, F Feng, Y Ma, K Li, TS Chua, Q He Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 36 | 2023 |
| Revisiting graph adversarial attack and defense from a data distribution perspective K Li, Y Liu, X Ao, Q He The Eleventh International Conference on Learning Representations, 2023 | 35 | 2023 |
| Explainable Graph-based Fraud Detection via Neural Meta-graph Search Z Qin, Y Liu, Q He, X Ao Proceedings of the 31st ACM International Conference on Information …, 2022 | 24 | 2022 |
| Alike and Unlike: Resolving Class Imbalance Problem in Financial Credit Risk Assessment Y Liu, X Ao, Q Zhong, J Feng, J Tang, Q He Proceedings of the 29th ACM International Conference on Information …, 2020 | 24 | 2020 |
| UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs Y Liu, X Ao, F Feng, Q He Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 22 | 2022 |
| Temporal high-order proximity aware behavior analysis on Ethereum X Ao, Y Liu, Z Qin, Y Sun, Q He World Wide Web 24 (5), 1565-1585, 2021 | 18 | 2021 |
| Spatiotemporal activity modeling via hierarchical cross-modal embedding Y Liu, X Ao, L Dong, C Zhang, J Wang, Q He IEEE Transactions on Knowledge and Data Engineering 34 (1), 462-474, 2020 | 15 | 2020 |
| Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective K Li, YW Chen, Y Liu, J Wang, Q He, M Cheng, X Ao The Twelfth International Conference on Learning Representations, 2024 | 10 | 2024 |
| Bi-level selection via meta gradient for graph-based fraud detection L Dong, Y Liu, X Ao, J Chi, J Feng, H Yang, Q He International Conference on Database Systems for Advanced Applications, 387-394, 2022 | 10 | 2022 |
| Improving fraud detection via imbalanced graph structure learning L Ren, R Hu, Y Liu, D Li, J Wu, Y Zang, W Hu Machine Learning 113 (3), 1069-1090, 2024 | 4 | 2024 |
| Free-rider episode screening via dual partition model X Ao, Y Liu, Z Huang, L Zuo, Q He Database Systems for Advanced Applications: 23rd International Conference …, 2018 | 3 | 2018 |
| F2GNN: An Adaptive Filter with Feature Segmentation for Graph-Based Fraud Detection G Hu, Y Liu, Q He, X Ao ICASSP 2024-2024 IEEE International Conference on Acoustics, Speech and …, 2024 | 1 | 2024 |
Qing HeInstitute of Computing Technology,Chinese Academy of SciencesПотвърден имейл адрес: ict.ac.cn