| Phishing scams detection in ethereum transaction network L Chen, J Peng, Y Liu, J Li, F Xie, Z Zheng ACM Transactions on Internet Technology (TOIT) 21 (1), 1-16, 2020 | 120 | 2020 |
| A survey of adversarial learning on graphs L Chen, J Li, J Peng, T Xie, Z Cao, K Xu, X He, Z Zheng, B Wu arXiv preprint arXiv:2003.05730, 2020 | 95 | 2020 |
| Adversarial attack on large scale graph J Li, T Xie, L Chen, F Xie, X He, Z Zheng IEEE Transactions on Knowledge and Data Engineering 35 (1), 82-95, 2021 | 61 | 2021 |
| Understanding structural vulnerability in graph convolutional networks L Chen, J Li, Q Peng, Y Liu, Z Zheng, C Yang arXiv preprint arXiv:2108.06280, 2021 | 51 | 2021 |
| What's Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders J Li, R Wu, W Sun, L Chen, S Tian, L Zhu, C Meng, Z Zheng, W Wang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 46* | 2023 |
| Spiking graph convolutional networks Z Zhu, J Peng, J Li, L Chen, Q Yu, S Luo arXiv preprint arXiv:2205.02767, 2022 | 34 | 2022 |
| 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 | 23 | 2022 |
| Spectral adversarial training for robust graph neural network J Li, J Peng, L Chen, Z Zheng, T Liang, Q Ling IEEE Transactions on Knowledge and Data Engineering, 2022 | 14 | 2022 |
| Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack ZZ Jintang Li, Bingzhe Wu, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen ... arXiv preprint arXiv:2202.07114, 2022 | 13* | 2022 |
| Scaling up dynamic graph representation learning via spiking neural networks J Li, Z Yu, Z Zhu, L Chen, Q Yu, Z Zheng, S Tian, R Wu, C Meng Proceedings of the AAAI Conference on Artificial Intelligence 37 (7), 8588-8596, 2023 | 11 | 2023 |
| Neighboring backdoor attacks on graph convolutional network L Chen, Q Peng, J Li, Y Liu, J Chen, Y Li, Z Zheng arXiv preprint arXiv:2201.06202, 2022 | 10 | 2022 |
| Unifying multi-associations through hypergraph for bundle recommendation Z Yu, J Li, L Chen, Z Zheng Knowledge-Based Systems 255, 109755, 2022 | 9 | 2022 |
| Graphgallery: A platform for fast benchmarking and easy development of graph neural networks based intelligent software J Li, K Xu, L Chen, Z Zheng, X Liu 2021 IEEE/ACM 43rd International Conference on Software Engineering …, 2021 | 8 | 2021 |
| 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 | 7 | 2022 |
| Graph enhanced neural interaction model for recommendation L Chen, T Xie, J Li, Z Zheng Knowledge-Based Systems 246, 108616, 2022 | 7 | 2022 |
| Sad: Semi-supervised anomaly detection on dynamic graphs S Tian, J Dong, J Li, W Zhao, X Xu, B Song, C Meng, T Zhang, L Chen arXiv preprint arXiv:2305.13573, 2023 | 6 | 2023 |
| Less can be more: Unsupervised graph pruning for large-scale dynamic graphs J Li, S Tian, R Wu, L Zhu, W Zhao, C Meng, L Chen, Z Zheng, H Yin arXiv preprint arXiv:2305.10673, 2023 | 5 | 2023 |
| Guard: Graph universal adversarial defense J Li, J Liao, R Wu, L Chen, Z Zheng, J Dan, C Meng, W Wang Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 3 | 2023 |
| A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks J Li, H Zhang, R Wu, Z Zhu, L Chen, Z Zheng, B Wang, C Meng arXiv preprint arXiv:2305.19306, 2023 | 2 | 2023 |
| Rethinking and Simplifying Bootstrapped Graph Latents W Sun, J Li, L Chen, B Wu, Y Bian, Z Zheng Proceedings of the 17th ACM International Conference on Web Search and Data …, 2024 | 1 | 2024 |
Liang ChenAssociate Professor, Sun Yat-Sen UniversityVerified email at mail.sysu.edu.cn
