Johannes Bordne

Uncertainty Estimation for Heterophilic Graphs Through the Lens of Information Theory

While uncertainty estimation for graphs recently gained traction, most methods rely on homophily and deteriorate in heterophilic settings. We address this by analyzing message passing neural networks from an information-theoretic perspective and developing a suitable analog to data processing in…