| Graph neural network-based anomaly detection in multivariate time series A Deng, B Hooi Proceedings of the AAAI conference on artificial intelligence 35 (5), 4027-4035, 2021 | 910 | 2021 |
| Deep long-tailed learning: A survey Y Zhang, B Kang, B Hooi, S Yan, J Feng IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (9), 10795 …, 2023 | 583 | 2023 |
| Rev2: Fraudulent user prediction in rating platforms S Kumar, B Hooi, D Makhija, M Kumar, C Faloutsos, VS Subrahmanian Proceedings of the Eleventh ACM International Conference on Web Search and …, 2018 | 451 | 2018 |
| Fraudar: Bounding graph fraud in the face of camouflage B Hooi, HA Song, A Beutel, N Shah, K Shin, C Faloutsos Proceedings of the 22nd ACM SIGKDD international conference on knowledge …, 2016 | 407 | 2016 |
| Beatgan: Anomalous rhythm detection using adversarially generated time series. B Zhou, S Liu, B Hooi, X Cheng, J Ye IJCAI 2019, 4433-4439, 2019 | 281 | 2019 |
| Can llms express their uncertainty? an empirical evaluation of confidence elicitation in llms M Xiong, Z Hu, X Lu, Y Li, J Fu, J He, B Hooi arXiv preprint arXiv:2306.13063, 2023 | 201 | 2023 |
| Mixup for node and graph classification Y Wang, W Wang, Y Liang, Y Cai, B Hooi Proceedings of the Web Conference 2021, 3663-3674, 2021 | 188 | 2021 |
| Birdnest: Bayesian inference for ratings-fraud detection B Hooi, N Shah, A Beutel, S Günnemann, L Akoglu, M Kumar, D Makhija, ... Proceedings of the 2016 SIAM International Conference on Data Mining, 495-503, 2016 | 161 | 2016 |
| Nodeaug: Semi-supervised node classification with data augmentation Y Wang, W Wang, Y Liang, Y Cai, J Liu, B Hooi Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 156 | 2020 |
| Understanding and resolving performance degradation in deep graph convolutional networks K Zhou, Y Dong, K Wang, WS Lee, B Hooi, H Xu, J Feng Proceedings of the 30th ACM International Conference on Information …, 2021 | 143* | 2021 |
| Self-supervised aggregation of diverse experts for test-agnostic long-tailed recognition Y Zhang, B Hooi, L Hong, J Feng Advances in Neural Information Processing Systems 35, 34077-34090, 2022 | 129 | 2022 |
| STP-UDGAT: Spatial-temporal-preference user dimensional graph attention network for next POI recommendation N Lim, B Hooi, SK Ng, X Wang, YL Goh, R Weng, J Varadarajan Proceedings of the 29th ACM International conference on information …, 2020 | 120 | 2020 |
| A general suspiciousness metric for dense blocks in multimodal data M Jiang, A Beutel, P Cui, B Hooi, S Yang, C Faloutsos 2015 IEEE International Conference on Data Mining, 781-786, 2015 | 118 | 2015 |
| Midas: Microcluster-based detector of anomalies in edge streams S Bhatia, B Hooi, M Yoon, K Shin, C Faloutsos Proceedings of the AAAI conference on artificial intelligence 34 (04), 3242-3249, 2020 | 117 | 2020 |
| M-zoom: Fast dense-block detection in tensors with quality guarantees K Shin, B Hooi, C Faloutsos Joint european conference on machine learning and knowledge discovery in …, 2016 | 116 | 2016 |
| Flowscope: Spotting money laundering based on graphs X Li, S Liu, Z Li, X Han, C Shi, B Hooi, H Huang, X Cheng Proceedings of the AAAI conference on artificial intelligence 34 (04), 4731-4738, 2020 | 112 | 2020 |
| Lunar: Unifying local outlier detection methods via graph neural networks A Goodge, B Hooi, SK Ng, WS Ng Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6737-6745, 2022 | 109 | 2022 |
| Fast and accurate anomaly detection in dynamic graphs with a two-pronged approach M Yoon, B Hooi, K Shin, C Faloutsos Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 97 | 2019 |
| Holoscope: Topology-and-spike aware fraud detection S Liu, B Hooi, C Faloutsos Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 93 | 2017 |
| Graph-based fraud detection in the face of camouflage B Hooi, K Shin, HA Song, A Beutel, N Shah, C Faloutsos ACM Transactions on Knowledge Discovery from Data (TKDD) 11 (4), 1-26, 2017 | 88 | 2017 |
