| Traffic speed prediction for urban transportation network: A path based deep learning approach J Wang, R Chen, Z He Transportation Research Part C: Emerging Technologies 100, 372-385, 2019 | 101 | 2019 |
| Spatial-temporal traffic speed patterns discovery and incomplete data recovery via SVD-combined tensor decomposition X Chen, Z He, J Wang Transportation research part C: emerging technologies 86, 59-77, 2018 | 78 | 2018 |
| Missing traffic data imputation and pattern discovery with a Bayesian augmented tensor factorization model X Chen, Z He, Y Chen, Y Lu, J Wang Transportation Research Part C: Emerging Technologies 104, 66-77, 2019 | 68 | 2019 |
| Dynamic holding control to avoid bus bunching: A multi-agent deep reinforcement learning framework J Wang, L Sun Transportation Research Part C: Emerging Technologies 116, 102661, 2020 | 46 | 2020 |
| Reducing Bus Bunching with Asynchronous Multi-Agent Reinforcement Learning J Wang, L Sun IJCAI 2021, Proceedings of the 30th International Joint Conference on …, 2021 | 2 | 2021 |
| Towards efficient connected and automated driving system via multi-agent graph reinforcement learning T Shi, J Wang, Y Wu, L Sun arXiv e-prints, arXiv: 2007.02794, 2020 | 2 | 2020 |
| Multi-agent graph reinforcement learning for connected automated Driving J Wang, T Shi, Y Wu, L Miranda-Moreno, L Sun ICML 2020 Workshop on AI for Autonomous Driving (AIAD), 2020 | 2 | 2020 |
| A Universal Framework of Spatiotemporal Bias Block for Long-Term Traffic Forecasting F Liu, J Wang, J Tian, D Zhuang, L Miranda-Moreno, L Sun IEEE Transactions on Intelligent Transportation Systems, 2022 | | 2022 |
Lijun Sun (孙立君)Assistant Professor, McGill UniversityVerified email at mcgill.ca
