2026
Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors
ICLR 2026poster
One of the most challenging problems in graph machine learning is generalizing across graphs with diverse properties. Graph neural networks (GNNs) face a fundamental limitation: they require separate training for each new graph, preventing universal generalization across diverse graph datasets. A cr…