2 papers
cs.LG2026
Treatment Effect Estimation with Differentiated Networked Effect on Graph Data
Xiaofeng Lin, Han Bao, Hisashi Kashima
Estimating individual treatment effect (ITE) from observational graph data is crucial for decision-making in the fields such as commerce and medicine. This task is challenging due…
cs.LG2025
Robust Anomaly Detection Under Normality Distribution Shift in Dynamic Graphs
Xiaoyang Xu, Xiaofeng Lin, Koh Takeuchi +2
Anomaly detection in dynamic graphs is a critical task with broad real-world applications, including social networks, e-commerce, and cybersecurity. Most existing methods assume th…