40 citations · 44 across the 3 of their papers we have counts for
3 papers
cs.LG2022★ 4 cited
Mutual Distillation Learning Network for Trajectory-User Linking
Wei Chen, Shuzhe Li, Chao Huang +3
Trajectory-User Linking (TUL), which links trajectories to users who generate them, has been a challenging problem due to the sparsity in check-in mobility data. Existing methods i…
cs.LG2022
Scalable Motif Counting for Large-scale Temporal Graphs
Zhongqiang Gao, Chuanqi Cheng, Yanwei Yu +3
One fundamental problem in temporal graph analysis is to count the occurrences of small connected subgraph patterns (i.e., motifs), which benefits a broad range of real-world appli…
cs.LG2019★ 40 cited
Joint Modeling of Dense and Incomplete Trajectories for Citywide Traffic Volume Inference
Xianfeng Tang, Boqing Gong, Yanwei Yu +4
Real-time traffic volume inference is key to an intelligent city. It is a challenging task because accurate traffic volumes on the roads can only be measured at certain locations w…