25 citations · 29 across the 12 of their papers we have counts for
6 papers · 1 filter
Rethinking Multi-View Fusion for Urban Representation Learning
Sean Bin Yang, Zongyi Xu, Jilin Hu +5
Urban region representation learning encodes heterogeneous urban signals, such as mobility flows, points of interest, and land-use patterns, into unified embeddings for downstream…
When Correlations Mislead: Confounder-Aware Multi-View Urban Region Representation Learning
Sean Bin Yang, Ying Sun, Zongyi Xu +6
Urban region representation learning commonly combines heterogeneous data sources, such as mobility flows, points of interest, and land-use information, to support tasks including…
REFINE: Trajectory Representation Learning via Closed-Loop Transcription -- Extended Version
Sean Bin Yang, Ying Sun, Jilin Hu +5
Trajectory representation learning underpins a wide range of trajectory analytics tasks; however, most existing self-supervised approaches, whether discriminative or generative, ad…
Spatio-Temporal Trajectory Foundation Model - Recent Advances and Future Directions
Sean Bin Yang, Ying Sun, Yunyao Cheng +3
Foundation models (FMs) have emerged as a powerful paradigm, enabling a diverse range of data analytics and knowledge discovery tasks across scientific fields. Inspired by the succ…
MH-GIN: Multi-scale Heterogeneous Graph-based Imputation Network for AIS Data (Extended Version)
Hengyu Liu, Tianyi Li, Yuqiang He +3
Location-tracking data from the Automatic Identification System, much of which is publicly available, plays a key role in a range of maritime safety and monitoring applications. Ho…
On Network Embedding for Machine Learning on Road Networks: A Case Study on the Danish Road Network
Tobias Skovgaard Jepsen, Christian S. Jensen, Thomas Dyhre Nielsen
Road networks are a type of spatial network, where edges may be associated with qualitative information such as road type and speed limit. Unfortunately, such information is often…