9 citations · 28 across the 8 of their papers we have counts for
4 papers · 1 filter
CDGNet: A Cross-Time Dynamic Graph-based Deep Learning Model for Traffic Forecasting
Yuchen Fang, Yanjun Qin, Haiyong Luo +4
Traffic forecasting is important in intelligent transportation systems of webs and beneficial to traffic safety, yet is very challenging because of the complex and dynamic spatio-t…
Inductive Matrix Completion Using Graph Autoencoder
Wei Shen, Chuheng Zhang, Yun Tian +4
Recently, the graph neural network (GNN) has shown great power in matrix completion by formulating a rating matrix as a bipartite graph and then predicting the link between the cor…
Trade When Opportunity Comes: Price Movement Forecasting via Locality-Aware Attention and Iterative Refinement Labeling
Liang Zeng, Lei Wang, Hui Niu +3
Price movement forecasting, aimed at predicting financial asset trends based on current market information, has achieved promising advancements through machine learning (ML) method…
Context-Aware Sparse Deep Coordination Graphs
Tonghan Wang, Liang Zeng, Weijun Dong +3
Learning sparse coordination graphs adaptive to the coordination dynamics among agents is a long-standing problem in cooperative multi-agent learning. This paper studies this probl…