66 citations · 268 across the 18 of their papers we have counts for
4 papers · 1 filter
EXGC: Bridging Efficiency and Explainability in Graph Condensation
Junfeng Fang, Xinglin Li, Yongduo Sui +5
Graph representation learning on vast datasets, like web data, has made significant strides. However, the associated computational and storage overheads raise concerns. In sight of…
Alleviating Structural Distribution Shift in Graph Anomaly Detection
Yuan Gao, Xiang Wang, Xiangnan He +3
Graph anomaly detection (GAD) is a challenging binary classification problem due to its different structural distribution between anomalies and normal nodes -- abnormal nodes are a…
Robust Collaborative Filtering to Popularity Distribution Shift
An Zhang, Wenchang Ma, Jingnan Zheng +2
In leading collaborative filtering (CF) models, representations of users and items are prone to learn popularity bias in the training data as shortcuts. The popularity shortcut tri…
Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting
An Zhang, Fangfu Liu, Wenchang Ma +3
Under stringent model type and variable distribution assumptions, differentiable score-based causal discovery methods learn a directed acyclic graph (DAG) from observational data b…