Automated Spatio-Temporal Synchronous Modeling with Multiple Graphs for Traffic Prediction
Fuxian Li(Tsinghua University), Depeng Jin(Tsinghua University), Huan Yan(Tsinghua University), Guangyin Jin(National University of Defense Technology), Yue Liu(University of South Australia), Yong Li(Anhui Normal University)
Proceedings of the 31st ACM International Conference on Information & Knowledge Management
October 16, 2022
Cited by 41
Related Papers
A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions
|ACM Transactions on Recommender Systems|2023|647
Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution
|ACM Transactions on Knowledge Discovery from Data|2022|499
Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey
|IEEE Transactions on Knowledge and Data Engineering|2023|425
Edge Intelligence: Empowering Intelligence to the Edge of Network
|Proceedings of the IEEE|2021|246
Social-aware D2D communications: qualitative insights and quantitative analysis
|IEEE Communications Magazine|2014|231