| 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 | 445 | 2020 |
| ADBench: Anomaly Detection Benchmark X Hu, S Han, H Huang, M Jiang, Y Zhao Advances in Neural Information Processing Systems, 2022 | 410 | 2022 |
| ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions Z Li, Y Zhao, X Hu, N Botta, C Ionescu, GH Chen IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022 | 372 | 2022 |
| Optimal sparse decision trees X Hu, C Rudin, M Seltzer Advances in Neural Information Processing Systems, 2019 | 259 | 2019 |
| 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, 2022 | 105 | 2022 |
| SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection X Hu, Y Zhao, C Cheng, C Wang, C Wan, W Wang, J Yang, H Bai, Z Li, ... Conference on Machine Learning and Systems, 2021 | 81 | 2021 |
| Pygod: A python library for graph outlier detection K Liu, Y Dou, X Ding, X Hu, R Zhang, H Peng, L Sun, PS Yu Journal of Machine Learning Research, 2024 | 55 | 2024 |
| Weakly supervised anomaly detection: A survey M Jiang, C Hou, A Zheng, X Hu, S Han, H Huang, X He, PS Yu, Y Zhao arXiv preprint arXiv:2302.04549, 2023 | 46 | 2023 |
| Benchmarking node outlier detection on graphs K Liu, Y Dou, Y Zhao, X Ding, X Hu, R Zhang, K Ding, C Chen, H Peng, ... arXiv preprint arXiv:2206.10071, 2022 | 17 | 2022 |
| Adgym: Design choices for deep anomaly detection M Jiang, C Hou, A Zheng, S Han, H Huang, Q Wen, X Hu, Y Zhao Advances in Neural Information Processing Systems 36, 70179-70207, 2023 | 16 | 2023 |
| Language agnostic multilingual information retrieval with contrastive learning X Hu, X Chen, P Qi, D Kong, K Liu, WY Wang, Z Huang arXiv preprint arXiv:2210.06633, 2022 | 11 | 2022 |
| Uncovering the source of machine bias X Hu, Y Huang, B Li, T Lu arXiv preprint arXiv:2201.03092, 2022 | 9 | 2022 |
| Uncovering the Source of Evaluation Bias in Micro-Lending X Hu, Y Huang, B Li, T Lu International Conference on Information Systems, 2021 | 9 | 2021 |
| Political-llm: Large language models in political science L Li, J Li, C Chen, F Gui, H Yang, C Yu, Z Wang, J Cai, JA Zhou, B Shen, ... arXiv preprint arXiv:2412.06864, 2024 | 4 | 2024 |
| Drugagent: Automating ai-aided drug discovery programming through llm multi-agent collaboration S Liu, Y Lu, S Chen, X Hu, J Zhao, T Fu, Y Zhao arXiv preprint arXiv:2411.15692, 2024 | 4 | 2024 |
| Inclusive fintech lending via contrastive learning and domain adaptation X Hu, Y Huang, B Li, T Lu arXiv preprint arXiv:2305.05827, 2023 | 4 | 2023 |
| Human-Algorithmic Bias: Source, Evolution, and Impact X Hu, Y Huang, B Li, T Lu Available at SSRN: https://ssrn.com/abstract=4195014, 2022 | 3 | 2022 |
| Credit Risk Modeling without Sensitive Features: An Adversarial Deep Learning Model for Fairness and Profit X Hu, Y Huang, B Li, T Lu International Conference on Information Systems, 2022 | 3 | 2022 |
| NLP-ADBench: NLP Anomaly Detection Benchmark Y Li, J Li, Z Xiao, T Yang, Y Nian, X Hu, Y Zhao arXiv preprint arXiv:2412.04784, 2024 | 2 | 2024 |
| Towards More Accurate US Presidential Election via Multi-step Reasoning with Large Language Models C Yu, Z Weng, Z Li, X Hu, Y Zhao arXiv preprint arXiv:2411.03321, 2024 | 2* | 2024 |
George H. ChenAssociate Professor, Carnegie Mellon UniversityВерификована је имејл адреса на cmu.edu