| DiffSTG: Probabilistic spatio-temporal graph forecasting with denoising diffusion models H Wen, Y Lin, Y Xia, H Wan, Q Wen, R Zimmermann, Y Liang Proceedings of the 31st ACM SigSpatial, 2023 | 27 | 2023 |
| Package pick-up route prediction via modeling couriers’ spatial-temporal behaviors H Wen, Y Lin, F Wu, H Wan, S Guo, L Wu, C Song, Y Xu 2021 IEEE 37th International Conference on Data Engineering (ICDE), 2141-2146, 2021 | 26 | 2021 |
| Graph2route: A dynamic spatial-temporal graph neural network for pick-up and delivery route prediction H Wen, Y Lin, X Mao, F Wu, Y Zhao, H Wang, J Zheng, L Wu, H Hu, ... Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 18 | 2022 |
| Deciphering spatio-temporal graph forecasting: A causal lens and treatment Y Xia, Y Liang, H Wen, X Liu, K Wang, Z Zhou, R Zimmermann Advances in Neural Information Processing Systems 36, 2024 | 17 | 2024 |
| Deeproute+: Modeling couriers’ spatial-temporal behaviors and decision preferences for package pick-up route prediction H Wen, Y Lin, H Wan, S Guo, F Wu, L Wu, C Song, Y Xu ACM Transactions on Intelligent Systems and Technology (TIST) 13 (2), 1-23, 2022 | 10 | 2022 |
| When urban region profiling meets large language models Y Yan, H Wen, S Zhong, W Chen, H Chen, Q Wen, R Zimmermann, ... WWW, 2023 | 9 | 2023 |
| Spatial-temporal position-aware graph convolution networks for traffic flow forecasting Y Zhao, Y Lin, H Wen, T Wei, X Jin, H Wan IEEE Transactions on Intelligent Transportation Systems, 2022 | 9 | 2022 |
| Traffic Inflow and Outflow Forecasting by Modeling Intra-and Inter-Relationship Between Flows Y Zhao, Y Lin, Y Zhang, H Wen, Y Liu, H Wu, Z Wu, S Zhang, H Wan IEEE Transactions on Intelligent Transportation Systems, 2022 | 8 | 2022 |
| Enough waiting for the couriers: Learning to estimate package pick-up arrival time from couriers’ spatial-temporal behaviors H Wen, Y Lin, F Wu, H Wan, Z Sun, T Cai, H Liu, S Guo, J Zheng, C Song, ... ACM Transactions on Intelligent Systems and Technology 14 (3), 1-22, 2023 | 4 | 2023 |
| Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook X Zou, Y Yan, X Hao, Y Hu, H Wen, E Liu, J Zhang, Y Li, T Li, Y Zheng, ... arXiv preprint arXiv:2402.19348, 2024 | 3 | 2024 |
| Lade: The first comprehensive last-mile delivery dataset from industry L Wu, H Wen, H Hu, X Mao, Y Xia, E Shan, J Zhen, J Lou, Y Liang, L Yang, ... arXiv preprint arXiv:2306.10675, 2023 | 3 | 2023 |
| Modeling intra-and inter-community information for route and time prediction in last-mile delivery Y Qiang, H Wen, L Wu, X Mao, F Wu, H Wan, H Hu 2023 IEEE 39th International Conference on Data Engineering (ICDE), 3106-3112, 2023 | 3 | 2023 |
| Modeling Spatial–Temporal Constraints and Spatial-Transfer Patterns for Couriers’ Package Pick-up Route Prediction H Wen, Y Lin, Y Hu, F Wu, M Xia, X Zhang, L Wu, H Hu, H Wan IEEE Transactions on Intelligent Transportation Systems, 2023 | 2 | 2023 |
| Drl4route: A deep reinforcement learning framework for pick-up and delivery route prediction X Mao, H Wen, H Zhang, H Wan, L Wu, J Zheng, H Hu, Y Lin Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 2 | 2023 |
| GMDNet: A Graph-Based Mixture Density Network for Estimating Packages’ Multimodal Travel Time Distribution X Mao, H Wan, H Wen, F Wu, J Zheng, Y Qiang, S Guo, L Wu, H Hu, Y Lin Proceedings of the AAAI Conference on Artificial Intelligence 37 (4), 4561-4568, 2023 | 2 | 2023 |
| G2ptl: A pre-trained model for delivery address and its applications in logistics system L Wu, J Liu, J Lou, H Hu, J Zheng, H Wen, C Song, S He arXiv preprint arXiv:2304.01559, 2023 | 2 | 2023 |
| EasyST: Modeling Spatial-Temporal Correlations and Uncertainty for Dynamic Wind Power Forecasting via PaddlePaddle Y Zhao, H Wen, J Lou, J Fu, J Zheng, Y Lin KDD workshop, 2022 | 2 | 2022 |
| Context-aware distance measures for dynamic networks Y Zhao, Y Lin, Z Wu, Y Wang, H Wen ACM Transactions on the Web (TWEB) 16 (1), 1-34, 2021 | 2 | 2021 |
| Deep Learning for Trajectory Data Management and Mining: A Survey and Beyond W Chen, Y Liang, Y Zhu, Y Chang, K Luo, H Wen, L Li, Y Yu, Q Wen, ... arXiv preprint arXiv:2403.14151, 2024 | 1 | 2024 |
| DynST: Dynamic Sparse Training for Resource-Constrained Spatio-Temporal Forecasting H Wu, H Wen, G Zhang, Y Xia, K Wang, Y Liang, Y Zheng, K Wang arXiv preprint arXiv:2403.02914, 2024 | 1 | 2024 |
Youfang Lin（林友芳）Beijing Jiaotong UniversityZweryfikowany adres z bjtu.edu.cn
