| Spatial-temporal graph attention networks: A deep learning approach for traffic forecasting C Zhang, JQ James, Y Liu Ieee Access 7, 166246-166256, 2019 | 188 | 2019 |
| FASTGNN: A topological information protected federated learning approach for traffic speed forecasting C Zhang, S Zhang, JQ James, S Yu IEEE Transactions on Industrial Informatics 17 (12), 8464-8474, 2021 | 143 | 2021 |
| Challenges and future directions of secure federated learning: a survey K Zhang, X Song, C Zhang, S Yu Frontiers of computer science 16, 1-8, 2022 | 111 | 2022 |
| A communication-efficient federated learning scheme for iot-based traffic forecasting C Zhang, L Cui, S Yu, JQ James IEEE Internet of Things Journal 9 (14), 11918-11931, 2021 | 40 | 2021 |
| Fedgru: Privacy-preserving traffic flow prediction via federated learning Y Liu, S Zhang, C Zhang, JQ James 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 35 | 2020 |
| Toward crowdsourced transportation mode identification: A semisupervised federated learning approach C Zhang, Y Zhu, C Markos, S Yu, JQ James IEEE Internet of Things Journal 9 (14), 11868-11882, 2021 | 33 | 2021 |
| Long-term origin-destination demand prediction with graph deep learning X Zou, S Zhang, C Zhang, JQ James, E Chung IEEE Transactions on Big Data 8 (6), 1481-1495, 2021 | 28 | 2021 |
| Bfu: Bayesian federated unlearning with parameter self-sharing W Wang, Z Tian, C Zhang, A Liu, S Yu Proceedings of the 2023 ACM Asia Conference on Computer and Communications …, 2023 | 20 | 2023 |
| Generative adversarial networks: A survey on attack and defense perspective C Zhang, S Yu, Z Tian, JJQ Yu ACM Computing Surveys 56 (4), 1-35, 2023 | 19 | 2023 |
| Learn travel time distribution with graph deep learning and generative adversarial network X Song, C Zhang, JQ James 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021 | 19 | 2021 |
| Complicating the social networks for better storytelling: An empirical study of Chinese historical text and novel C Zhang, Q Zhang, S Yu, JQ James, X Song IEEE Transactions on Computational Social Systems 8 (3), 754-767, 2021 | 18 | 2021 |
| Graph-based traffic forecasting via communication-efficient federated learning C Zhang, S Zhang, S Yu, JQ James 2022 IEEE Wireless Communications and Networking Conference (WCNC), 2041-2046, 2022 | 16 | 2022 |
| TSTNet: A sequence to sequence transformer network for spatial-temporal traffic prediction X Song, Y Wu, C Zhang Artificial Neural Networks and Machine Learning–ICANN 2021: 30th …, 2021 | 14 | 2021 |
| An enhanced motif graph clustering-based deep learning approach for traffic forecasting C Zhang, S Zhang, JQ James, S Yu GLOBECOM 2020-2020 IEEE Global Communications Conference, 1-6, 2020 | 13 | 2020 |
| Machine Unlearning: A Comprehensive Survey W Wang, Z Tian, C Zhang, S Yu arXiv preprint arXiv:2405.07406, 2024 | 12 | 2024 |
| Origin-destination matrix prediction via hexagon-based generated graph Y Yang, S Zhang, C Zhang, JQ James 2021 IEEE International Intelligent Transportation Systems Conference (ITSC …, 2021 | 10 | 2021 |
| Security and privacy in federated learning S Yu, L Cui | 9 | 2023 |
| Machine unlearning via representation forgetting with parameter self-sharing W Wang, C Zhang, Z Tian, S Yu IEEE Transactions on Information Forensics and Security, 2023 | 8 | 2023 |
| Toward large-scale graph-based traffic forecasting: A data-driven network partitioning approach C Zhang, S Zhang, X Zou, S Yu, JQ James IEEE Internet of Things Journal 10 (5), 4506-4519, 2022 | 8 | 2022 |
| Attention-driven recurrent imputation for traffic speed S Zhang, C Zhang, S Zhang, JQ James IEEE Open Journal of Intelligent Transportation Systems 3, 723-737, 2022 | 8 | 2022 |
James Jianqiao Yu 余剑峤Harbin Institute of Technology, ShenzhenVerified email at hit.edu.cn