| How to build a graph-based deep learning architecture in traffic domain: A survey J Ye, J Zhao, K Ye, C Xu IEEE Transactions on Intelligent Transportation Systems 23 (5), 3904-3924, 2020 | 225 | 2020 |
| Spatio-temporal analysis of passenger travel patterns in massive smart card data J Zhao, Q Qu, F Zhang, C Xu, S Liu IEEE Transactions on Intelligent Transportation Systems 18 (11), 3135-3146, 2017 | 192 | 2017 |
| Estimation of passenger route choice pattern using smart card data for complex metro systems J Zhao, F Zhang, L Tu, C Xu, D Shen, C Tian, XY Li, Z Li IEEE Transactions on Intelligent Transportation Systems 18 (4), 790-801, 2016 | 135 | 2016 |
| UrbanCPS: A cyber-physical system based on multi-source big infrastructure data for heterogeneous model integration D Zhang, J Zhao, F Zhang, T He Proceedings of the ACM/IEEE Sixth International Conference on Cyber-Physical …, 2015 | 95 | 2015 |
| Spatiotemporal segmentation of metro trips using smart card data F Zhang, J Zhao, C Tian, C Xu, X Liu, L Rao IEEE Transactions on Vehicular Technology 65 (3), 1137-1149, 2015 | 57 | 2015 |
| Multi-graph convolutional network for relationship-driven stock movement prediction J Ye, J Zhao, K Ye, C Xu 2020 25th International Conference on Pattern Recognition (ICPR), 6702-6709, 2021 | 56 | 2021 |
| A characterization of big data benchmarks W Xiong, Z Yu, Z Bei, J Zhao, F Zhang, Y Zou, X Bai, Y Li, C Xu 2013 IEEE international conference on big data, 118-125, 2013 | 56 | 2013 |
| Employing opportunistic charging for electric taxicabs to reduce idle time L Yan, H Shen, Z Li, A Sarker, JA Stankovic, C Qiu, J Zhao, C Xu Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2018 | 49 | 2018 |
| CatCharger: Deploying wireless charging lanes in a metropolitan road network through categorization and clustering of vehicle traffic L Yan, H Shen, J Zhao, C Xu, F Luo, C Qiu IEEE INFOCOM 2017-IEEE conference on computer communications, 1-9, 2017 | 49 | 2017 |
| Multi-stgcnet: A graph convolution based spatial-temporal framework for subway passenger flow forecasting J Ye, J Zhao, K Ye, C Xu 2020 International joint conference on neural networks (IJCNN), 1-8, 2020 | 45 | 2020 |
| comobile: Real-time human mobility modeling at urban scale using multi-view learning D Zhang, J Zhao, F Zhang, T He Proceedings of the 23rd SIGSPATIAL international conference on advances in …, 2015 | 44 | 2015 |
| Understanding temporal and spatial travel patterns of individual passengers by mining smart card data J Zhao, C Tian, F Zhang, C Xu, S Feng 17th International IEEE Conference on Intelligent Transportation Systems …, 2014 | 43 | 2014 |
| Coscal: Multifaceted scaling of microservices with reinforcement learning M Xu, C Song, S Ilager, SS Gill, J Zhao, K Ye, C Xu IEEE Transactions on Network and Service Management 19 (4), 3995-4009, 2022 | 30 | 2022 |
| Feeder: supporting last-mile transit with extreme-scale urban infrastructure data D Zhang, J Zhao, F Zhang, R Jiang, T He Proceedings of the 14th International Conference on Information Processing …, 2015 | 29 | 2015 |
| Spatiotemporal data fusion in graph convolutional networks for traffic prediction B Zhao, X Gao, J Liu, J Zhao, C Xu Ieee Access 8, 76632-76641, 2020 | 22 | 2020 |
| Investigating physical encounters of individuals in urban metro systems with large-scale smart card data K Liu, L Yin, Z Ma, F Zhang, J Zhao Physica A: Statistical Mechanics and its Applications 545, 123398, 2020 | 21 | 2020 |
| Heterogeneous model integration for multi-source urban infrastructure data D Zhang, J Zhao, F Zhang, T He, H Lee, SH Son ACM Transactions on Cyber-Physical Systems 1 (1), 1-26, 2016 | 18 | 2016 |
| Learning the unlearnable: Adversarial augmentations suppress unlearnable example attacks T Qin, X Gao, J Zhao, K Ye, CZ Xu arXiv preprint arXiv:2303.15127, 2023 | 17 | 2023 |
| Last-mile transit service with urban infrastructure data D Zhang, J Zhao, F Zhang, R Jiang, T He, N Papanikolopoulos ACM Transactions on Cyber-Physical Systems 1 (2), 1-26, 2016 | 15 | 2016 |
| Completion and augmentation-based spatiotemporal deep learning approach for short-term metro origin-destination matrix prediction under limited observable data J Ye, J Zhao, F Zheng, C Xu Neural Computing and Applications 35 (4), 3325-3341, 2023 | 11 | 2023 |
Chengzhong Xu, IEEE FellowUniversity of Macau, Macau SAR, China在 um.edu.mo 的电子邮件经过验证
