3 citations · 8 across the 5 of their papers we have counts for
4 papers · 1 filter
Multi-Scale Spatial-Temporal Recurrent Networks for Traffic Flow Prediction
Haiyang Liu, Chunjiang Zhu, Detian Zhang +1
Traffic flow prediction is one of the most fundamental tasks of intelligent transportation systems. The complex and dynamic spatial-temporal dependencies make the traffic flow pred…
STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
Xunlian Luo, Chunjiang Zhu, Detian Zhang +1
Traffic prediction has been an active research topic in the domain of spatial-temporal data mining. Accurate real-time traffic prediction is essential to improve the safety, stabil…
Attention-based Spatial-Temporal Graph Convolutional Recurrent Networks for Traffic Forecasting
Haiyang Liu, Chunjiang Zhu, Detian Zhang +1
Traffic forecasting is one of the most fundamental problems in transportation science and artificial intelligence. The key challenge is to effectively model complex spatial-tempora…
Dynamic Graph Convolutional Network with Attention Fusion for Traffic Flow Prediction
Xunlian Luo, Chunjiang Zhu, Detian Zhang +1
Accurate and real-time traffic state prediction is of great practical importance for urban traffic control and web mapping services. With the support of massive data, deep learning…