| Safety in graph machine learning: Threats and safeguards S Wang, Y Dong, B Zhang, Z Chen, X Fu, Y He, C Shen, C Zhang, ... arXiv preprint arXiv:2405.11034, 2024 | 16 | 2024 |
| Causal inference with latent variables: Recent advances and future prospectives Y Zhu, Y He, J Ma, M Hu, S Li, J Li Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 3 | 2024 |
| Explaining graph neural networks with large language models: A counterfactual perspective on molecule graphs Y He, Z Zheng, P Soga, Y Zhu, Y Dong, J Li Findings of the Association for Computational Linguistics: EMNLP 2024, 7079-7096, 2024 | 2 | 2024 |
| Spectral greedy coresets for graph neural networks M Ding, Y He, J Li, F Huang arXiv preprint arXiv:2405.17404, 2024 | 1 | 2024 |
| Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking from A Spectral Perspective Y Dong, P Soga, Y He, S Wang, J Li arXiv preprint arXiv:2412.07188, 2024 | | 2024 |
| Global Graph Counterfactual Explanation: A Subgraph Mapping Approach Y He, W Zheng, Y Zhu, J Ma, S Mishra, N Raman, N Liu, J Li https://arxiv.org/abs/2410.19978, 2024 | | 2024 |
| Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction Y He, Z Zheng, P Soga, Y Zhu, Y Dong, J Li Conference on Empirical Methods in Natural Language Processing (EMNLP …, 2024 | | 2024 |
| Demystify Epidemic Containment in Directed Networks: Theory and Algorithms Y He, C Chen, S Wang, G Min, J Li ACM International Conference on Web Search and Data Mining (WSDM), 2025, 0 | | |
Jundong LiAssistant Professor, University of VirginiaPatvirtintas el. paštas virginia.edu