Spatio-Temporal Graph Neural Networks for Predictive Learning in Urban Computing: A Survey

Guangyin Jin(National University of Defense Technology), Yu Zheng(Changsha University), Yuchen Fang(University of Electronic Science and Technology of China), Junbo Zhang(Microsoft Research Asia (China)), Jincai Huang(National University of Defense Technology), Zezhi Shao(University of Chinese Academy of Sciences), Yuxuan Liang(Guangdong Ocean University)
IEEE Transactions on Knowledge and Data Engineering
November 23, 2023
10.1109/tkde.2023.3333824
Cited by 425

Related Papers

Predicting citywide crowd flows using deep spatio-temporal residual networks
|Artificial Intelligence|2018|517
Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution
|ACM Transactions on Knowledge Discovery from Data|2022|499
Forecasting Fine-Grained Air Quality Based on Big Data
|Unknown|2015|472
Decoupled dynamic spatial-temporal graph neural network for traffic forecasting
|Proceedings of the VLDB Endowment|2022|329
Deep Distributed Fusion Network for Air Quality Prediction
|Unknown|2018|325