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2020 – today
- 2023
[j5]Guangyin Jin, Hengyu Sha, Zhexu Xi, Jincai Huang:
Urban hotspot forecasting via automated spatio-temporal information fusion. Appl. Soft Comput. 136: 110087 (2023)- 2022
- [j4]Guangyin Jin
, Min Wang, Jinlei Zhang, Hengyu Sha, Jincai Huang:
STGNN-TTE: Travel time estimation via spatial-temporal graph neural network. Future Gener. Comput. Syst. 126: 70-81 (2022) - [j3]Guangyin Jin, Zhexu Xi, Hengyu Sha, Yanghe Feng, Jincai Huang:
Deep multi-view graph-based network for citywide ride-hailing demand prediction. Neurocomputing 510: 79-94 (2022) - [j2]Guangyin Jin, Chenxi Liu, Zhexu Xi, Hengyu Sha, Yanyun Liu, Jincai Huang:
Adaptive Dual-View WaveNet for urban spatial-temporal event prediction. Inf. Sci. 588: 315-330 (2022) - 2021
- [j1]Guangyin Jin, Hengyu Sha, Yanghe Feng, Qing Cheng, Jincai Huang:
GSEN: An ensemble deep learning benchmark model for urban hotspots spatiotemporal prediction. Neurocomputing 455: 353-367 (2021) - [c1]Hengyu Sha, Guangyin Jin, Guangquan Cheng, Jincai Huang, Kuihua Huang:
A Deep Urban Hotspots Prediction Framework with Modeling Geography-Semantic Dynamics. SpatialDI 2021: 3-14 - 2020
- [i1]Guangyin Jin, Zhexu Xi, Hengyu Sha, Yanghe Feng, Jincai Huang:
Deep Multi-View Spatiotemporal Virtual Graph Neural Network for Significant Citywide Ride-hailing Demand Prediction. CoRR abs/2007.15189 (2020)
Coauthor Index
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