| Learning graph representation by aggregating subgraphs via mutual information maximization C Wang, Z Liu arXiv preprint arXiv:2103.13125, 2021 | 18 | 2021 |
| A game-theoretic approach for improving generalization ability of TSP solvers C Wang, Y Yang, O Slumbers, C Han, T Guo, H Zhang, J Wang ICLR 2022 Workshop: Gamification and Multiagent Solutions (Spotlight), 2021 | 13 | 2021 |
| ASP: Learn a Universal Neural Solver! C Wang, Z Yu, S McAleer, T Yu, Y Yang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 9 | 2024 |
| Solving uncapacitated P-Median problem with reinforcement learning assisted by graph attention networks C Wang, C Han, T Guo, M Ding Applied Intelligence 53 (2), 2010-2025, 2023 | 8 | 2023 |
| Efficient training of multi-task neural solver with multi-armed bandits C Wang, T Yu arXiv preprint arXiv:2305.06361, 2023 | 3 | 2023 |
| Exploring over-smoothing in graph attention networks from the Markov chain perspective W Zhao, C Wang, C Han, T Guo Proceedings of the 2023 International Conference on Frontiers of Artificial …, 2023 | 2 | 2023 |
| Understanding Oversmoothing in Diffusion-Based GNNs From the Perspective of Operator Semigroup Theory W Zhao, C Wang, X Wang, C Han, T Guo, T Yu arXiv preprint arXiv:2402.15326, 2024 | | 2024 |
| Towards Principled Task Grouping for Multi-Task Learning C Wang, X Pan, T Yu arXiv preprint arXiv:2402.15328, 2024 | | 2024 |
| Learning Graph Representation by Aggregating Subgraphs via Mutual Information Maximization Z Liu, C Wang, C Han, T Guo Neurocomputing, 126392, 2023 | | 2023 |
| Analysis of Graph Neural Networks with Theory of Markov Chains. W Zhao, C Wang, C Han, T Guo CoRR, 2022 | | 2022 |
Congying HanProfessor,University of Chinese Academy of SciencesVerified email at ucas.ac.cn
