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 | 48 | 2023 |
Foundation models for time series analysis: A tutorial and survey Y Liang, H Wen, Y Nie, Y Jiang, M Jin, D Song, S Pan, Q Wen Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 47 | 2024 |
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 | 34 | 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 | 32 | 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 | 31 | 2024 |
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 24 (8), 8650-8666, 2022 | 21 | 2022 |
A survey on diffusion models for time series and spatio-temporal data Y Yang, M Jin, H Wen, C Zhang, Y Liang, L Ma, Y Wang, C Liu, B Yang, ... arXiv preprint arXiv:2404.18886, 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 | 16 | 2022 |
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, ... Information Fusion 113, 102606, 2025 | 13 | 2025 |
Urbanclip: Learning text-enhanced urban region profiling with contrastive language-image pretraining from the web Y Yan, H Wen, S Zhong, W Chen, H Chen, Q Wen, R Zimmermann, ... Proceedings of the ACM on Web Conference 2024, 4006-4017, 2024 | 13 | 2024 |
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 | 13 | 2024 |
When urban region profiling meets large language models Y Yan, H Wen, S Zhong, W Chen, H Chen, Q Wen, R Zimmermann, ... WWW, 2023 | 13 | 2023 |
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 | 12 | 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 | 9 | 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 | 7 | 2023 |
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, ... KDD 2024, 2023 | 6 | 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 | 5 | 2023 |
A survey on service route and time prediction in instant delivery: Taxonomy, progress, and prospects H Wen, Y Lin, L Wu, X Mao, T Cai, Y Hou, S Guo, Y Liang, G Jin, Y Zhao, ... IEEE Transactions on Knowledge and Data Engineering, 2024 | 4 | 2024 |
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 | 4 | 2023 |
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 | 3 | 2024 |