| Inductive graph neural networks for spatiotemporal kriging Y Wu, D Zhuang, A Labbe, L Sun Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4478-4485, 2020 | 115 | 2020 |
| Uncertainty quantification of sparse travel demand prediction with spatial-temporal graph neural networks D Zhuang, S Wang, H Koutsopoulos, J Zhao Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 30 | 2022 |
| Low-rank Hankel tensor completion for traffic speed estimation X Wang, Y Wu, D Zhuang, L Sun IEEE Transactions on Intelligent Transportation Systems, 2021 | 29 | 2021 |
| Understanding the bike sharing travel demand and cycle lane network: The case of Shanghai D Zhuang, JG Jin, Y Shen, W Jiang International journal of sustainable transportation 15 (2), 111-123, 2021 | 22 | 2021 |
| Spatial aggregation and temporal convolution networks for real-time kriging Y Wu, D Zhuang, M Lei, A Labbe, L Sun arXiv preprint arXiv:2109.12144, 2021 | 21 | 2021 |
| From compound word to metropolitan station: Semantic similarity analysis using smart card data D Zhuang, S Hao, DH Lee, JG Jin Transportation Research Part C: Emerging Technologies 114, 322-337, 2020 | 17 | 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 23 (10), 19064-19075, 2022 | 12 | 2022 |
| Uncertainty quantification of spatiotemporal travel demand with probabilistic graph neural networks Q Wang, S Wang, D Zhuang, H Koutsopoulos, J Zhao IEEE Transactions on Intelligent Transportation Systems, 2024 | 11 | 2024 |
| Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction X Jiang, D Zhuang, X Zhang, H Chen, J Luo, X Gao Proceeding of CIKM 2023, 2023 | 7 | 2023 |
| Spatiotemporal graph neural networks with uncertainty quantification for traffic incident risk prediction X Gao, X Jiang, D Zhuang, H Chen, S Wang, J Haworth arXiv preprint arXiv:2309.05072, 2023 | 6 | 2023 |
| Large Language Models for Travel Behavior Prediction B Mo, H Xu, D Zhuang, R Ma, X Guo, J Zhao arXiv preprint arXiv:2312.00819, 2023 | 5 | 2023 |
| ST-GIN: An Uncertainty Quantification Approach in Traffic Data Imputation with Spatio-temporal Graph Attention and Bidirectional Recurrent United Neural Networks Z Wang, D Zhuang, Y Li, J Zhao, P Sun Proceeding of the 26th IEEE International Conference on Intelligent …, 2023 | 5 | 2023 |
| Fairness-enhancing deep learning for ride-hailing demand prediction Y Zheng, Q Wang, D Zhuang, S Wang, J Zhao IEEE Open Journal of Intelligent Transportation Systems, 2023 | 5 | 2023 |
| Synergizing Spatial Optimization with Large Language Models for Open-Domain Urban Itinerary Planning Y Tang, Z Wang, A Qu, Y Yan, K Hou, D Zhuang, X Guo, J Zhao, Z Zhao, ... arXiv preprint arXiv:2402.07204, 2024 | 3 | 2024 |
| Fairness-Enhancing Vehicle Rebalancing in the Ride-hailing System X Guo, H Xu, D Zhuang, Y Zheng, J Zhao arXiv preprint arXiv:2401.00093, 2023 | 3 | 2023 |
| The Braess Paradox in Dynamic Traffic D Zhuang, Y Huang, V Jayawardana, J Zhao, D Suo, C Wu 2022 IEEE 25th International Conference on Intelligent Transportation …, 2022 | 3 | 2022 |
| Timeseries Suppliers Allocation Risk Optimization via Deep Black Litterman Model J Luo, W Zhang, Y Fang, X Gao, D Zhuang, H Chen, X Jiang arXiv preprint arXiv:2401.17350, 2024 | 1 | 2024 |
| SAUC: Sparsity-Aware Uncertainty Calibration for Spatiotemporal Prediction with Graph Neural Networks D Zhuang, Y Bu, G Wang, S Wang, J Zhao Neural Information Processing Systems (NeurIPS) Temporal Graph Learning …, 2023 | 1 | 2023 |
| Advancing Transportation Mode Share Analysis with Built Environment: Deep Hybrid Models with Urban Road Network D Zhuang, Q Wang, Y Zheng, X Guo, S Wang, HN Koutsopoulos, J Zhao arXiv preprint arXiv:2405.14079, 2024 | | 2024 |
Jinhua ZhaoDepartment of Urban Studies and Planning, MIT在 mit.edu 的电子邮件经过验证
