A Recipe for Causal Graph Regression: Confounding Effects Revisited

Yujia Yin, Tianyi Qu, Zihao Wang +1

Through recognizing causal subgraphs, causal graph learning (CGL) has risen to be a promising approach for improving the generalizability of graph neural networks under out-of-dist…