| STGCN: a spatial-temporal aware graph learning method for POI recommendation H Han, M Zhang, M Hou, F Zhang, Z Wang, E Chen, H Wang, J Ma, Q Liu 2020 IEEE International Conference on Data Mining (ICDM), 1052-1057, 2020 | 81 | 2020 |
| Label-free node classification on graphs with large language models (llms) Z Chen, H Mao, H Wen, H Han, W Jin, H Zhang, H Liu, J Tang arXiv preprint arXiv:2310.04668, 2023 | 71 | 2023 |
| Demystifying structural disparity in graph neural networks: Can one size fit all? H Mao, Z Chen, W Jin, H Han, Y Ma, T Zhao, N Shah, J Tang Advances in neural information processing systems 36, 37013-37067, 2023 | 64 | 2023 |
| Amazon-m2: A multilingual multi-locale shopping session dataset for recommendation and text generation W Jin, H Mao, Z Li, H Jiang, C Luo, H Wen, H Han, H Lu, Z Wang, R Li, ... Advances in Neural Information Processing Systems 36, 8006-8026, 2023 | 42 | 2023 |
| Constructing educational concept maps with multiple relationships from multi-source data X Huang, Q Liu, C Wang, H Han, J Ma, E Chen, Y Su, S Wang 2019 IEEE International Conference on Data Mining (ICDM), 1108-1113, 2019 | 28 | 2019 |
| Lazygnn: Large-scale graph neural networks via lazy propagation R Xue, H Han, MA Torkamani, J Pei, X Liu International Conference on Machine Learning, 38926-38937, 2023 | 22 | 2023 |
| Alternately optimized graph neural networks H Han, X Liu, H Mao, MA Torkamani, F Shi, V Lee, J Tang International Conference on Machine Learning, 12411-12429, 2023 | 12 | 2023 |
| Retrieval-augmented generation with graphs (graphrag) H Han, Y Wang, H Shomer, K Guo, J Ding, Y Lei, M Halappanavar, ... arXiv preprint arXiv:2501.00309, 2024 | 10 | 2024 |
| Mixture of Link Predictors on Graphs L Ma, H Han, J Li, H Shomer, H Liu, X Gao, J Tang arXiv preprint arXiv:2402.08583, 2024 | 8* | 2024 |
| Enhancing graph representations learning with decorrelated propagation H Liu, H Han, W Jin, X Liu, H Liu Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 8 | 2023 |
| Node-wise filtering in graph neural networks: A mixture of experts approach H Han, J Li, W Huang, X Tang, H Lu, C Luo, H Liu, J Tang arXiv preprint arXiv:2406.03464, 2024 | 5 | 2024 |
| Towards label position bias in graph neural networks H Han, X Liu, F Shi, MA Torkamani, C Aggarwal, J Tang Advances in Neural Information Processing Systems 36, 22999-23018, 2023 | 5 | 2023 |
| Augment with care: Enhancing graph contrastive learning with selective spectrum perturbation K Yang, H Han, W Jin, H Liu arXiv preprint arXiv:2310.13845, 2023 | 4 | 2023 |
| Enhancing ID and Text Fusion via Alternative Training in Session-based Recommendation J Li, H Han, Z Chen, H Shomer, W Jin, A Javari, J Tang arXiv preprint arXiv:2402.08921, 2024 | 3 | 2024 |
| Structural fairness-aware active learning for graph neural networks H Han, X Liu, L Ma, MA Torkamani, H Liu, J Tang, M Yamada The Twelfth International Conference on Learning Representations, 2024 | 3 | 2024 |
| Unleashing the Power of LLMs as Multi-Modal Encoders for Text and Graph-Structured Data J Lin, K Qian, H Han, N Choudhary, T Wei, Z Wang, S Genc, EW Huang, ... arXiv preprint arXiv:2410.11235, 2024 | 2 | 2024 |
| Reasoning with Graphs: Structuring Implicit Knowledge to Enhance LLMs Reasoning H Han, Y Xie, H Liu, X Tang, S Nag, W Headden, Y Li, C Luo, S Ji, Q He, ... arXiv preprint arXiv:2501.07845, 2025 | 1 | 2025 |
| Spectral-Aware Augmentation for Enhanced Graph Representation Learning K Yang, H Han, W Jin, H Liu Proceedings of the 33rd ACM International Conference on Information and …, 2024 | 1 | 2024 |
| Large-Scale Graph Neural Networks: The Past and New Frontiers R Xue, H Han, T Zhao, N Shah, J Tang, X Liu Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 1 | 2023 |
| Graph Neural Networks as Multi-View Learning H Han, X Liu, H Mao, MA Torkamani, F Shi, V Lee, J Tang | 1 | 2022 |
Jiliang TangUniversity Foundation Professor of Computer Science and Engineering, Michigan State UniversityVerified email at msu.edu
