arXiv stat.ML
· Papers
Conformal Graph Prediction with Z-Gromov-Wasserstein Distances
arXiv:2603.02460v5 Announce Type: replace 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 gra