2 papers
cs.LG2026
Rethinking Efficient Graph Coarsening via a Non-Selfishness Principle
Xu Bai, Bin Lu, Kun Zhang +4
Graph coarsening is a graph dimensionality reduction technique that aims to construct a smaller and more tractable graph while preserving the essential structural and semantic prop…
stat.ML2026
CGRL: Causal-Guided Representation Learning for Node-Level Out-of-Distribution Generalization
Bowen Lu, Lianqiang Yang, Liangqiang Yang +2
Graph Neural Networks (GNNs) deliver strong performance on graph tasks, but their accuracy drops significantly under out-of-distribution (OOD) scenarios. Under distribution shifts,…