15 citations · 16 across the 2 of their papers we have counts for
3 papers
cs.LG2021★ 1 cited
Network-wide link travel time and station waiting time estimation using automatic fare collection data: A computational graph approach
Jinlei Zhang, Feng Chen, Lixing Yang +3
Urban rail transit (URT) system plays a dominating role in many megacities like Beijing and Hong Kong. Due to its important role and complex nature, it is always in great need for…
cs.LG2021
Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution
Fuxian Li, Jie Feng, Huan Yan +3
Traffic prediction is the cornerstone of an intelligent transportation system. Accurate traffic forecasting is essential for the applications of smart cities, i.e., intelligent tra…
cs.LG2020★ 15 cited
Deep Multi-View Spatiotemporal Virtual Graph Neural Network for Significant Citywide Ride-hailing Demand Prediction
Guangyin Jin, Zhexu Xi, Hengyu Sha +2
Urban ride-hailing demand prediction is a crucial but challenging task for intelligent transportation system construction. Predictable ride-hailing demand can facilitate more reaso…