3 citations · 4 across the 3 of their papers we have counts for
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cs.LG2025
GeoMAE: Masking Representation Learning for Spatio-Temporal Graph Forecasting with Missing Values
Songyu Ke, Chenyu Wu, Yuxuan Liang +3
The ubiquity of missing data in urban intelligence systems, attributable to adverse environmental conditions and equipment failures, poses a significant challenge to the efficacy o…
cs.LG2023★ 1 cited
Spatio-Temporal Contrastive Self-Supervised Learning for POI-level Crowd Flow Inference
Songyu Ke, Ting Li, Li Song +4
Accurate acquisition of crowd flow at Points of Interest (POIs) is pivotal for effective traffic management, public service, and urban planning. Despite this importance, due to the…