| Metapath-guided heterogeneous graph neural network for intent recommendation S Fan, J Zhu, X Han, C Shi, L Hu, B Ma, Y Li Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 329 | 2019 |
| Harnessing the power of llms in practice: A survey on chatgpt and beyond J Yang, H Jin, R Tang, X Han, Q Feng, H Jiang, S Zhong, B Yin, X Hu ACM Transactions on Knowledge Discovery from Data, 2023 | 247 | 2023 |
| G-mixup: Graph data augmentation for graph classification X Han, Z Jiang, N Liu, X Hu International Conference on Machine Learning, 8230-8248, 2022 | 127 | 2022 |
| Deep collaborative filtering with multi-aspect information in heterogeneous networks C Shi, X Han, L Song, X Wang, S Wang, J Du, SY Philip IEEE transactions on knowledge and data engineering 33 (4), 1413-1425, 2019 | 114 | 2019 |
| Aspect-Level Deep Collaborative Filtering via Heterogeneous Information Networks. X Han, C Shi, S Wang, SY Philip, L Song IJCAI 18, 3393-3399, 2018 | 99 | 2018 |
| 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 | 88 | 2020 |
| Does synthetic data generation of llms help clinical text mining? R Tang, X Han, X Jiang, X Hu arXiv preprint arXiv:2303.04360, 2023 | 74 | 2023 |
| Generalized demographic parity for group fairness Z Jiang, X Han, C Fan, F Yang, A Mostafavi, X Hu International Conference on Learning Representations, 2022 | 53 | 2022 |
| Anomalous trajectory detection using recurrent neural network L Song, R Wang, D Xiao, X Han, Y Cai, C Shi Advanced Data Mining and Applications: 14th International Conference, ADMA …, 2018 | 47 | 2018 |
| Fmp: Toward fair graph message passing against topology bias Z Jiang, X Han, C Fan, Z Liu, N Zou, A Mostafavi, X Hu arXiv preprint arXiv:2202.04187, 2022 | 39 | 2022 |
| Mlpinit: Embarrassingly simple gnn training acceleration with mlp initialization X Han, T Zhao, Y Liu, X Hu, N Shah International Conference on Learning Representations, 2022 | 25 | 2022 |
| Geometric graph representation learning via maximizing rate reduction X Han, Z Jiang, N Liu, Q Song, J Li, X Hu Proceedings of the ACM Web Conference 2022, 1226-1237, 2022 | 21 | 2022 |
| Autorec: An automated recommender system TH Wang, X Hu, H Jin, Q Song, X Han, Z Liu Proceedings of the 14th ACM Conference on Recommender Systems, 582-584, 2020 | 20 | 2020 |
| Auto-PINN: understanding and optimizing physics-informed neural architecture Y Wang, X Han, CY Chang, D Zha, U Braga-Neto, X Hu arXiv preprint arXiv:2205.13748, 2022 | 15 | 2022 |
| Retiring DP: New Distribution-Level Metrics for Demographic Parity X Han, Z Jiang, H Jin, Z Liu, N Zou, Q Wang, X Hu Transactions on Machine Learning Research, 2023 | 13 | 2023 |
| Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach ZS Jiang, X Han, H Jin, G Wang, R Chen, N Zou, X Hu Advances in Neural Information Processing Systems 36, 2024 | 9* | 2024 |
| Llm maybe longlm: Self-extend llm context window without tuning H Jin, X Han, J Yang, Z Jiang, Z Liu, CY Chang, H Chen, X Hu arXiv preprint arXiv:2401.01325, 2024 | 9 | 2024 |
| Representation learning with depth and breadth for recommendation using multi-view data X Han, C Shi, L Zheng, PS Yu, J Li, Y Lu Web and Big Data: Second International Joint Conference, APWeb-WAIM 2018 …, 2018 | 8 | 2018 |
| Embedding geographic information for anomalous trajectory detection D Xiao, L Song, R Wang, X Han, Y Cai, C Shi World Wide Web 23 (5), 2789-2809, 2020 | 6 | 2020 |
| Understanding and optimizing physics-informed neural architecture Y Wang, X Han, CY Chang, D Zha, U Braga-Neto, XAP Hu arXiv preprint arXiv:2205.13748, 2022 | 5 | 2022 |
Xia "Ben" HuAssociate Professor of Computer Science, Rice UniversityVerified email at rice.edu
