| Learning with Hilbert–Schmidt independence criterion: A review and new perspectives T Wang, X Dai, Y Liu Knowledge-Based Systems 234, 107567, 2021 | 37 | 2021 |
| STFL: A temporal-spatial federated learning framework for graph neural networks G Lou, Y Liu, T Zhang, X Zheng DLG-AAAI'2022, 2021 | 17 | 2021 |
| An Adaptive Federated Relevance Framework for Spatial Temporal Graph Learning T Zhang*, Y Liu*, Z Shen, R Xu, X Chen, X Huang, X Zheng IEEE Transactions on Artificial Intelligence, 2023 | 9* | 2023 |
| AstBERT: Enabling Language Model for Code Understanding with Abstract Syntax Tree R Liang, Y Lu, Z Huang, T Zhang, Y Liu EMNLP, 2022 | 5* | 2022 |
| GPS: A Policy-driven Sampling Approach for Graph Representation Learning T Zhang, Y Liu, X Chen, X Huang, F Zhu, X Zheng DLG-KDD'2022, 2021 | 5 | 2021 |
| Learning from Heterogeneity: A Dynamic Learning Framework for Hypergraphs T Zhang*, Y Liu*, Z Shen, X Ma, X Chen, X Huang, J Yin, J Jin arXiv preprint arXiv:2307.03411, 2023 | 4 | 2023 |
| Exploiting Spatial-temporal Data for Sleep Stage Classification via Hypergraph Learning Y Liu*, Z Zhao*, T Zhang, K Wang, X Chen, X Huang, J Yin, Z Shen ICASSP2024, 2023 | 3 | 2023 |
| Towards Relation-centered Pooling and Convolution for Heterogeneous Graph Learning Networks T Zhang*, Y Liu*, Y Yao, Y Xia, X Chen, X Huang, J Jin DLG-AAAI'2023, 2022 | 2 | 2022 |
| DSHGT : Dual-Supervisors Heterogeneous Graph Transformer - A pioneer study of using heterogeneous graph learning for detecting software vulnerabilities XZ Tiehua Zhang, Rui Xu, Jianping Zhang, Yuzhe Liu, Xin Chen, Jun Yin ACM Transactions on Software Engineering and Methodology, 2024 | 1 | 2024 |
| GRL-Prompt: Towards Knowledge Graph based Prompt Optimization via Reinforcement Learning Y Liu, T Liu, T Zhang, Y Xia, J Wang, Z Shen, J Jin, FR Yu arXiv preprint arXiv:2411.14479, 2024 | | 2024 |
Tiehua ZhangSchool of Computer Science and Technology, Tongji University在 swin.edu.au 的电子邮件经过验证
