| Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework C Yang, J Liu, C Shi Proceedings of the Web Conference 2021, 1227--1237, 2021 | 150 | 2021 |
| Towards graph foundation models: A survey and beyond J Liu, C Yang, Z Lu, J Chen, Y Li, M Zhang, T Bai, Y Fang, L Sun, PS Yu, ... arXiv preprint arXiv:2310.11829, 2023 | 82 | 2023 |
| A survey on heterogeneous information network based recommender systems: Concepts, methods, applications and resources J Liu, C Shi, C Yang, Z Lu, PS Yu AI Open 3 (2022), 40-57, 2022 | 53 | 2022 |
| Decorrelated Clustering with Data Selection Bias X Wang, S Fan, K Kuang, C Shi, J Liu, B Wang Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 17 | 2020 |
| Learning to distill graph neural networks C Yang, Y Guo, Y Xu, C Shi, J Liu, C Wang, X Li, N Guo, H Yin Proceedings of the sixteenth ACM international conference on web search and …, 2023 | 10 | 2023 |
| 基于异质信息网络的推荐系统研究综述 刘佳玮， 石川， 杨成， 菲利普 信息安全学报 6 (5), 1-16, 2021 | 5 | 2021 |
| Heterogeneous spatio-temporal graph contrastive learning for point-of-interest recommendation J Liu, H Gao, C Yang, C Shi, T Yang, H Cheng, Q Xie, X Wang, D Wang Tsinghua Science and Technology 30 (1), 186-197, 2024 | 4 | 2024 |
| Self-Supervised Spatio-Temporal Graph Learning for Point-of-Interest Recommendation J Liu, H Gao, C Shi, H Cheng, Q Xie Applied Sciences 13 (15), 8885, 2023 | 4 | 2023 |
| Endowing Pre-trained Graph Models with Provable Fairness Z Zhang, M Zhang, Y Yu, C Yang, J Liu, C Shi Proceedings of the ACM on Web Conference 2024, 1045-1056, 2024 | 3 | 2024 |
| Abnormal event detection via hypergraph contrastive learning B Yan, C Yang, C Shi, J Liu, X Wang Proceedings of the 2023 SIAM International Conference on Data Mining (SDM …, 2023 | 3 | 2023 |
| Graph foundation model C Shi, J Chen, J Liu, C Yang Frontiers of Computer Science 18 (6), 186355, 2024 | 2 | 2024 |
| PGAU: Static IR Drop Analysis for Power Grid using Attention U-Net Architecture and Label Distribution Smoothing F Guo, J Liu, J Zhai, J Jia, K Zhao, C Shi Proceedings of the Great Lakes Symposium on VLSI 2024, 452-458, 2024 | 1 | 2024 |
| IR-Fusion: A Fusion Framework for Static IR Drop Analysis Combining Numerical Solution and Machine Learning F Guo, J Zhai, J Jia, J Liu, K Zhao, B Yu, C Shi IEEE/ACM Proceedings Design, Automation and Test in Europe (DATE), 2025 | | 2025 |
| PolarGate: Breaking the Functionality Representation Bottleneck of And-Inverter Graph Neural Network J Liu, J Zhai, M Zhao, Z Lin, B Yu, C Shi | | 2024 |
| Graph neural network based time estimator for SAT solver J Liu, W Xiao, H Cheng, C Shi International Journal of Machine Learning and Cybernetics, 1-12, 2024 | | 2024 |
| SATGL: An Open-Source Graph Learning Toolkit for Boolean Satisfiability HT Cheng, J Liu, J Zhai, M Zhao, C Yang, C Shi 2024 2nd International Symposium of Electronics Design Automation (ISEDA …, 2024 | | 2024 |
Chuan ShiBeijing University of Posts and Telecommunications在 bupt.edu.cn 的电子邮件经过验证