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eess.SP2025
Dirichlet Meets Horvitz and Thompson: Estimating Homophily in Large Networks via Sampling
Hamed Ajorlou, Gonzalo Mateos, Luana Ruiz
Assessing homophily in large-scale networks is central to understanding structural regularities in graphs, and thus inform the choice of models (such as graph neural networks) adop…
eess.SP2024
Sampling Transferable Graph Neural Networks with Limited Graph Information
Haoyu Wang, Renyuan Ma, Gonzalo Mateos +1
Graph neural networks (GNNs) achieve strong performance on graph learning tasks, but training on large-scale networks remains computationally challenging. Transferability results s…