| Graph Information Bottleneck for Subgraph Recognition J Yu, T Xu, Y Rong, Y Bian, J Huang, R He ICLR 2021, 2021 | 175* | 2021 |
| Improving Subgraph Recognition with Variational Graph Information Bottleneck J Yu, J Cao, R He CVPR 2022, 2022 | 57* | 2022 |
| Recognizing Predictive Substructures with Subgraph Information Bottleneck J Yu, T Xu, Y Rong, Y Bian, J Huang, R He IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 47 | 2021 |
| Pose-preserving Cross Spectral Face Hallucination. J Yu, J Cao, Y Li, X Jia, R He IJCAI, 1018-1024, 2019 | 42 | 2019 |
| A survey of trustworthy graph learning: Reliability, explainability, and privacy protection B Wu, J Li, J Yu, Y Bian, H Zhang, CH Chen, C Hou, G Fu, L Chen, T Xu, ... arXiv preprint arXiv:2205.10014, 2022 | 35 | 2022 |
| Mind the Label Shift of Augmentation-based Graph OOD generalization J Yu, J Liang, R He CVPR 2023, 2023 | 30* | 2023 |
| Structure-aware conditional variational auto-encoder for constrained molecule optimization J Yu, T Xu, Y Rong, J Huang, R He Pattern Recognition 126, 108581, 2022 | 28 | 2022 |
| Thought Propagation: An Analogical Approach to Complex Reasoning with Large Language Models J Yu, R He, R Ying ICLR 2024, 2024 | 24* | 2024 |
| Rumor Detection with Diverse Counterfactual Evidence K Zhang, J Yu, H Shi, J Liang, XY Zhang ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023 | 18 | 2023 |
| Scoremix: A scalable augmentation strategy for training gans with limited data J Cao, M Luo, J Yu, MH Yang, R He IEEE Transactions on pattern analysis and machine intelligence 45 (7), 8920-8935, 2022 | 14 | 2022 |
| Finding diverse and predictable subgraphs for graph domain generalization J Yu, J Liang, R He arXiv preprint arXiv:2206.09345, 2022 | 11 | 2022 |
| Trustworthy graph learning: Reliability, explainability, and privacy protection B Wu, Y Bian, H Zhang, J Li, J Yu, L Chen, C Chen, J Huang Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 9 | 2022 |
| Generative explanations for graph neural network: Methods and evaluations J Chen, K Amara, J Yu, R Ying arXiv preprint arXiv:2311.05764, 2023 | 5 | 2023 |
| Towards the explanation of graph neural networks in digital pathology with information flows J Yu, T Xu, R He arXiv preprint arXiv:2112.09895, 2021 | 5 | 2021 |
Ran He, IAPR/IEEE FellowNational Laboratory of Pattern Recognition, CASIAVerified email at nlpr.ia.ac.cn
