| PyOD: A Python Toolbox for Scalable Outlier Detection Y Zhao, Z Nasrullah, Z Li Journal of Machine Learning Research (JMLR) 20, 1-7, 2019 | 683 | 2019 |
| Diffusion Models: A Comprehensive Survey of Methods and Applications L Yang, Z Zhang, Y Song, S Hong, R Xu, Y Zhao, W Zhang, B Cui, ... ACM Computing Surveys, 2023 | 240 | 2023 |
| COPOD: copula-based outlier detection Z Li, Y Zhao, N Botta, C Ionescu, X Hu 2020 IEEE International Conference on Data Mining (ICDM), 1118-1123, 2020 | 212 | 2020 |
| Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development K Huang*, T Fu*, W Gao*, Y Zhao, Y Roohani, J Leskovec, CW Coley, ... Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 143* | 2021 |
| Employee Turnover Prediction with Machine Learning: A Reliable Approach Y Zhao, M Hryniewicki, F Cheng, X Fu, Boyang, Zhu Intelligent Systems Conference, 737-758, 2018 | 142 | 2018 |
| XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning Y Zhao, M Hryniewicki International Joint Conference on Neural Networks (IJCNN), 2018 | 130 | 2018 |
| LSCP: Locally selective combination in parallel outlier ensembles Y Zhao, Z Nasrullah, MK Hryniewicki, Z Li SIAM International Conference on Data Mining (SDM), 585-593, 2019 | 129 | 2019 |
| ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions Y Zhao*, Z Li*, X Hu, N Botta, C Ionescu, GH Chen IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022 | 122* | 2022 |
| ADBench: Anomaly Detection Benchmark S Han*, X Hu*, H Huang*, M Jiang*, Y Zhao* Advances in Neural Information Processing Systems (NeurIPS) 35, 2022 | 101 | 2022 |
| Revisiting Time Series Outlier Detection: Definitions and Benchmarks KH Lai, D Zha, J Xu, Y Zhao, G Wang, X Hu Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 85 | 2021 |
| Automatic Unsupervised Outlier Model Selection Y Zhao, R Rossi, L Akoglu Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 66* | 2021 |
| SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection Y Zhao*, X Hu*, C Cheng, C Wang, C Wan, W Wang, J Yang, H Bai, Z Li, ... Proceedings of Machine Learning and Systems (MLSys) 3, 2021 | 58* | 2021 |
| TODS: An Automated Time Series Outlier Detection System KH Lai, D Zha, G Wang, J Xu, Y Zhao, D Kumar, Y Chen, P Zumkhawaka, ... Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021 | 57 | 2021 |
| Music Artist Classification with Convolutional Recurrent Neural Networks Z Nasrullah, Y Zhao International Joint Conference on Neural Networks (IJCNN), 2019 | 55 | 2019 |
| Artificial intelligence foundation for therapeutic science K Huang, T Fu, W Gao, Y Zhao, Y Roohani, J Leskovec, CW Coley, ... Nature Chemical Biology 18 (10), 1033-1036, 2022 | 39 | 2022 |
| BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs K Liu*, Y Dou*, Y Zhao*, X Ding, X Hu, R Zhang, K Ding, C Chen, H Peng, ... Advances in Neural Information Processing Systems (NeurIPS) 35, 2022 | 34* | 2022 |
| DCSO: dynamic combination of detector scores for outlier ensembles Y Zhao, MK Hryniewicki KDD Workshop on Outlier Detection and Description, 2018 | 29* | 2018 |
| The Need for Unsupervised Outlier Model Selection: A Review and Evaluation of Internal Evaluation Strategies MQ Ma*, Y Zhao*, X Zhang, L Akoglu ACM SIGKDD Explorations Newsletter 25 (1), 19-35, 2023 | 24* | 2023 |
| Contrastive Attributed Network Anomaly Detection with Data Augmentation Z Xu, X Huang, Y Zhao, Y Dong, J Li Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2022 | 23 | 2022 |
| SynC: A Copula based Framework for Generating Synthetic Data from Aggregated Sources Z Li, Y Zhao, J Fu IEEE International Conference on Data Mining Workshops (ICDMW), 2020 | 22* | 2020 |
Leman AkogluAssociate Professor, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
