3 papers
cs.LG2026
Rethinking Feature Alignment in Generalist Graph Anomaly Detection: A Relational Fingerprint-based Approach
Yujing Liu, Yixin Liu, Yu Zheng +3
Generalist graph anomaly detection (GAD) aims to detect anomalies on unseen graphs without graph-specific retraining. Nevertheless, existing approaches primarily focus on aligning…
cs.LG2026
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.AI2025
M-STAR: Multi-Scale Spatiotemporal Autoregression for Human Mobility Modeling
Yuxiao Luo, Songming Zhang, Sijie Ruan +5
Modeling human mobility is vital for extensive applications such as transportation planning and epidemic modeling. With the rise of the Artificial Intelligence Generated Content (A…