Tag: gromov

Conformal Graph Prediction with Z-Gromov Wasserstein Distances arXiv:2603.02460v1 Announce Type: new Abstract: Supervised graph prediction addresses regression problems where the outputs are structured graphs. Although several approaches exist for graph–valued prediction, principled uncertainty quantification remains limited. We propose a conformal prediction framework for graph-valued outputs, providing distribution–free coverage guarantees in structured output spaces. Our method…