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cs.LG2025
From Moments to Models: Graphon-Mixture Learning for Mixup and Contrastive Learning
Ali Azizpour, Reza Ramezanpour, Santiago Segarra
Real-world graph datasets often arise from mixtures of populations, where graphs are generated by multiple distinct underlying distributions. In this work, we propose a unified fra…
cs.LG2025
A Few Moments Please: Scalable Graphon Learning via Moment Matching
Reza Ramezanpour, Victor M. Tenorio, Antonio G. Marques +2
Graphons, as limit objects of dense graph sequences, play a central role in the statistical analysis of network data. However, existing graphon estimation methods often struggle wi…