| Self-supervised graph-level representation learning with adversarial contrastive learning X Luo, W Ju, Y Gu, Z Mao, L Liu, Y Yuan, M Zhang ACM Transactions on Knowledge Discovery from Data 18 (2), 1-23, 2023 | 19 | 2023 |
| Alex: Towards effective graph transfer learning with noisy labels J Yuan, X Luo, Y Qin, Z Mao, W Ju, M Zhang Proceedings of the 31st ACM international conference on multimedia, 3647-3656, 2023 | 11 | 2023 |
| Zero-shot node classification with graph contrastive embedding network W Ju, Y Qin, S Yi, Z Mao, K Zheng, L Liu, X Luo, M Zhang Transactions on Machine Learning Research, 2023 | 11 | 2023 |
| Rahnet: Retrieval augmented hybrid network for long-tailed graph classification Z Mao, W Ju, Y Qin, X Luo, M Zhang Proceedings of the 31st ACM international conference on multimedia, 3817-3826, 2023 | 9 | 2023 |
| A survey of graph neural networks in real world: Imbalance, noise, privacy and ood challenges W Ju, S Yi, Y Wang, Z Xiao, Z Mao, H Li, Y Gu, Y Qin, N Yin, S Wang, ... arXiv preprint arXiv:2403.04468, 2024 | 8 | 2024 |
| A Survey on Graph Neural Networks in Intelligent Transportation Systems H Li, Y Zhao, Z Mao, YF Qin, Z Xiao, J Feng, Y Gu, W Ju, X Luo, M Zhang arXiv preprint arXiv:2401.00713, 2024 | 7 | 2024 |
| Rignn: A rationale perspective for semi-supervised open-world graph classification X Luo, Y Zhao, Z Mao, Y Qin, W Ju, M Zhang, Y Sun Transactions on Machine Learning Research, 2023 | 7 | 2023 |
| EvadeRL: Evading PDF malware classifiers with deep reinforcement learning Z Mao, Z Fang, M Li, Y Fan Security and Communication Networks 2022 (1), 7218800, 2022 | 6 | 2022 |
| Towards long-tailed recognition for graph classification via collaborative experts SY Yi, Z Mao, W Ju, YD Zhou, L Liu, X Luo, M Zhang IEEE Transactions on Big Data, 2023 | 4 | 2023 |
| Focus on informative graphs! Semi-supervised active learning for graph-level classification W Ju, Z Mao, Z Qiao, Y Qin, S Yi, Z Xiao, X Luo, Y Fu, M Zhang Pattern Recognition 153, 110567, 2024 | 2 | 2024 |
| Hypergraph-enhanced Dual Semi-supervised Graph Classification W Ju, Z Mao, S Yi, Y Qin, Y Gu, Z Xiao, Y Wang, X Luo, M Zhang arXiv preprint arXiv:2405.04773, 2024 | 1 | 2024 |
| DEER: Distribution Divergence-based Graph Contrast for Partial Label Learning on Graphs Y Gu, Z Chen, Y Qin, Z Mao, Z Xiao, W Ju, C Chen, XS Hua, Y Wang, ... IEEE Transactions on Multimedia, 2024 | | 2024 |
| Towards Graph Contrastive Learning: A Survey and Beyond W Ju, Y Wang, Y Qin, Z Mao, Z Xiao, J Luo, J Yang, Y Gu, D Wang, ... arXiv preprint arXiv:2405.11868, 2024 | | 2024 |
| GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling W Ju, Y Gu, Z Mao, Z Qiao, Y Qin, X Luo, H Xiong, M Zhang arXiv preprint arXiv:2401.16011, 2024 | | 2024 |
