| A survey on deep semi-supervised learning X Yang, Z Song, I King, Z Xu IEEE Transactions on Knowledge and Data Engineering 35 (9), 8934-8954, 2022 | 754 | 2022 |
| Graph-based semi-supervised learning: A comprehensive review Z Song, X Yang, Z Xu, I King IEEE Transactions on Neural Networks and Learning Systems 34 (11), 8174-8194, 2022 | 264 | 2022 |
| COSTA: covariance-preserving feature augmentation for graph contrastive learning Y Zhang, H Zhu, Z Song, P Koniusz, I King Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 130 | 2022 |
| Spectral feature augmentation for graph contrastive learning and beyond Y Zhang, H Zhu, Z Song, P Koniusz, I King Proceedings of the AAAI Conference on Artificial Intelligence 37 (9), 11289 …, 2023 | 93 | 2023 |
| MAC: Measuring the impacts of anomalies on travel time of multiple transportation systems Z Fang, Y Yang, S Wang, B Fu, Z Song, F Zhang, D Zhang Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2019 | 41 | 2019 |
| Towards an optimal asymmetric graph structure for robust semi-supervised node classification Z Song, Y Zhang, I King Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 36 | 2022 |
| Semi-supervised multi-label learning for graph-structured data Z Song, Z Meng, Y Zhang, I King Proceedings of the 30th ACM International Conference on Information …, 2021 | 32 | 2021 |
| A Survey on Vision-Language-Action Models for Embodied AI Y Ma, Z Song, Y Zhuang, J Hao, I King arXiv preprint arXiv:2405.14093, 2024 | 30 | 2024 |
| Hierarchical heterogeneous graph attention network for syntax-aware summarization Z Song, I King Proceedings of the AAAI Conference on Artificial Intelligence 36 (10), 11340 …, 2022 | 26 | 2022 |
| WSFE: wasserstein sub-graph feature encoder for effective user segmentation in collaborative filtering Y Chen, Y Zhang, M Yang, Z Song, C Ma, I King Proceedings of the 46th International ACM SIGIR Conference on Research and …, 2023 | 25 | 2023 |
| Mitigating the popularity bias of graph collaborative filtering: A dimensional collapse perspective Y Zhang, H Zhu, Z Song, P Koniusz, I King Advances in Neural Information Processing Systems 36, 67533-67550, 2023 | 22 | 2023 |
| Contrastive cross-scale graph knowledge synergy Y Zhang, Y Chen, Z Song, I King Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 20 | 2023 |
| Tackling Long-tailed Distribution Issue in Graph Neural Networks via Normalization L Liang, Z Xu, Z Song, I King, Y Qi, J Ye IEEE Transactions on Knowledge and Data Engineering, 2023 | 18 | 2023 |
| Predicting global label relationship matrix for graph neural networks under heterophily L Liang, X Hu, Z Xu, Z Song, I King Advances in Neural Information Processing Systems 36, 10909-10921, 2023 | 17 | 2023 |
| Towards fair financial services for all: A temporal GNN approach for individual fairness on transaction networks Z Song, Y Zhang, I King Proceedings of the 32nd ACM international conference on information and …, 2023 | 16 | 2023 |
| Graph component contrastive learning for concept relatedness estimation Y Ma, Z Song, X Hu, J Li, Y Zhang, I King Proceedings of the AAAI Conference on Artificial Intelligence 37 (11), 13362 …, 2023 | 15 | 2023 |
| Optimal block-wise asymmetric graph construction for graph-based semi-supervised learning Z Song, Y Zhang, I King Advances in Neural Information Processing Systems 36, 2024 | 12 | 2024 |
| Resnorm: Tackling long-tailed degree distribution issue in graph neural networks via normalization L Liang, Z Xu, Z Song, I King, J Ye arXiv preprint arXiv:2206.08181, 2022 | 12 | 2022 |
| No change, no gain: empowering graph neural networks with expected model change maximization for active learning Z Song, Y Zhang, I King Advances in Neural Information Processing Systems 36, 2024 | 9 | 2024 |
| Individual fairness in dynamic financial networks Z Song, Y Ma, I King NeurIPS 2022 Workshop: New Frontiers in Graph Learning, 2022 | 8 | 2022 |
