| Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning M Jin, Y Zheng, YF Li, C Gong, C Zhou, S Pan International Joint Conferences on Artificial Intelligence (IJCAI2021), 2022 | 178 | 2022 |
| Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination Y Zheng, S Pan, VC Lee, Y Zheng, PS Yu Advances in Neural Information Processing Systems 36, 2022 | 105 | 2022 |
| Beyond smoothing: Unsupervised graph representation learning with edge heterophily discriminating Y Liu, Y Zheng, D Zhang, VCS Lee, S Pan Proceedings of the AAAI conference on artificial intelligence 37 (4), 4516-4524, 2023 | 85 | 2023 |
| A Survey on Fairness-aware Recommender Systems D Jin, L Wang, H Zhang, Y Zheng, W Ding, F Xia, S Pan Information Fusion, 2023 | 48 | 2023 |
| Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-prone Graphs Y Zheng, H Zhang, V Lee, Y Zheng, X Wang, S Pan The Fortieth International Conference on Machine Learning (ICML), 2023 | 47 | 2023 |
| Large language models for scientific discovery in molecular property prediction Y Zheng, HY Koh, J Ju, ATN Nguyen, LT May, GI Webb, S Pan Nature Machine Intelligence, 1-11, 2025 | 42* | 2025 |
| Dual intent enhanced graph neural network for session-based new item recommendation D Jin, L Wang, Y Zheng, G Song, F Jiang, X Li, W Lin, S Pan Proceedings of the ACM web conference 2023, 684-693, 2023 | 37 | 2023 |
| Heterogeneous graph attention network for small and medium-sized enterprises bankruptcy prediction Y Zheng, VCS Lee, Z Wu, S Pan Pacific-Asia Conference on Knowledge Discovery and Data Mining, 140-151, 2022 | 37 | 2022 |
| Integrating Graphs with Large Language Models: Methods and Prospects S Pan, Y Zheng, Y Liu IEEE intelligent systems, 2024 | 28 | 2024 |
| CGMN: A Contrastive Graph Matching Network for Self-Supervised Graph Similarity Learning D Jin, L Wang, Y Zheng, X Li, F Jiang, W Lin, S Pan 31st International Joint Conference on Artificial Intelligence, IJCAI 2022, 2022 | 24 | 2022 |
| Towards graph self-supervised learning with contrastive adjusted zooming Y Zheng, M Jin, S Pan, YF Li, H Peng, M Li, Z Li IEEE Transactions on Neural Networks and Learning Systems, 2022 | 22 | 2022 |
| PREM: A Simple Yet Effective Approach for Node-Level Graph Anomaly Detection J Pan*, Y Liu*, Y Zheng*, S Pan IEEE International Conference on Data Mining (ICDM), 2023 | 19 | 2023 |
| Unifying Graph Contrastive Learning with Flexible Contextual Scopes Y Zheng, Y Zheng, X Zhou, C Gong, VCS Lee, S Pan IEEE International Conference on Data Mining, ICDM 2022, 2022 | 16 | 2022 |
| Contrastive Graph Similarity Networks L Wang*, Y Zheng*, D Jin, F Li, Y Qiao, S Pan ACM Transactions on the Web, 2023 | 15 | 2023 |
| Large language models in drug discovery and development: From disease mechanisms to clinical trials Y Zheng, HY Koh, M Yang, L Li, LT May, GI Webb, S Pan, G Church arXiv preprint arXiv:2409.04481, 2024 | 10 | 2024 |
| Improving augmentation consistency for graph contrastive learning W Bu, X Cao, Y Zheng, S Pan Pattern Recognition 148, 110182, 2024 | 10 | 2024 |
| Breaking the curse of dimensional collapse in graph contrastive learning: A whitening perspective Y Tao, K Guo, Y Zheng, S Pan, X Cao, Y Chang Information Sciences 657, 119952, 2024 | 4 | 2024 |
| Collaborative Expert LLMs Guided Multi-Objective Molecular Optimization J Yu, Y Zheng, HY Koh, S Pan, T Wang, H Wang arXiv preprint arXiv:2503.03503, 2025 | | 2025 |
| A Label-Free Heterophily-Guided Approach for Unsupervised Graph Fraud Detection J Pan, Y Liu, X Zheng, Y Zheng, AWC Liew, F Li, S Pan arXiv preprint arXiv:2502.13308, 2025 | | 2025 |
Shirui PanFull Professor, ARC Future Fellow, FQA, Director of TrustAGI Lab, Griffith UniversityVerified email at griffith.edu.au
