| Adaptive graph convolutional recurrent network for traffic forecasting L Bai, L Yao, C Li, X Wang, C Wang Advances in Neural Information Processing Systems 33, 17804-17815, 2020 | 1468 | 2020 |
| On the joint impact of high-speed rail and megalopolis policy on regional economic growth in China Z Yang, C Li, J Jiao, W Liu, F Zhang Transport Policy 99, 20-30, 2020 | 59 | 2020 |
| Graph neural network for robust public transit demand prediction C Li, L Bai, W Liu, L Yao, ST Waller IEEE Transactions on Intelligent Transportation Systems 23 (5), 4086-4098, 2020 | 48 | 2020 |
| A multi-task memory network with knowledge adaptation for multimodal demand forecasting C Li, L Bai, W Liu, L Yao, ST Waller Transportation Research Part C: Emerging Technologies 131, 103352, 2021 | 38 | 2021 |
| Knowledge adaption for demand prediction based on multi-task memory neural network C Li, L Bai, W Liu, L Yao, ST Waller Proceedings of the 29th ACM International Conference on Information …, 2020 | 32 | 2020 |
| Deep spatial–temporal sequence modeling for multi-step passenger demand prediction L Bai, L Yao, X Wang, C Li, X Zhang Future Generation Computer Systems 121, 25-34, 2021 | 30 | 2021 |
| Urban mobility analytics: A deep spatial–temporal product neural network for traveler attributes inference C Li, L Bai, W Liu, L Yao, ST Waller Transportation Research Part C: Emerging Technologies 124, 102921, 2021 | 24 | 2021 |
| A Bibliometric Analysis and Review on Reinforcement Learning for Transportation Applications C Li, L Bai, L Yao, ST Waller, W Liu Transportmetrica B: Transport Dynamics 11 (1), 1095-1135, 2023 | 14 | 2023 |
| Multimodal transport demand forecasting via federated learning C Li, W Liu IEEE Transactions on Intelligent Transportation Systems 25 (5), 4009-4020, 2023 | 10 | 2023 |
| Passenger demographic attributes prediction for human-centered public transport C Li, L Bai, W Liu, L Yao, ST Waller Neural Information Processing: 26th International Conference, ICONIP 2019 …, 2019 | 8 | 2019 |
| Mobility irregularity detection with smart transit card data X Wang, L Yao, W Liu, C Li, L Bai, ST Waller Advances in Knowledge Discovery and Data Mining: 24th Pacific-Asia …, 2020 | 4 | 2020 |
| Unsupervised Knowledge Adaptation for Passenger Demand Forecasting C Li, L Bai, W Liu, L Yao, ST Waller arXiv preprint arXiv:2206.04053, 2022 | 3 | 2022 |
| Learning and managing stochastic network traffic dynamics: an iterative and interactive approach Q He, M Ma, C Li, W Liu Transportmetrica B: Transport Dynamics 12 (1), 2303050, 2024 | 1 | 2024 |
| TimeKAN: KAN-based Frequency Decomposition Learning Architecture for Long-term Time Series Forecasting S Huang, Z Zhao, C Li, L Bai arXiv preprint arXiv:2502.06910, 2025 | | 2025 |
| Deep causal inference for understanding the impact of meteorological variations on traffic C Li, W Liu, H Yang Transportation Research Part C: Emerging Technologies 165, 104744, 2024 | | 2024 |
| Urban Mobility Analytics: Understanding, Inference and Forecasting C Li UNSW Sydney, 2022 | | 2022 |
Lei BaiShanghai AI LaboratoryVerified email at sydney.edu.au
