Preprint
Jul 2026
Graph Neural Networks for Scalable and Transferable Node Centrality Approximation
Results show that mixed-distribution training can improve structural transfer in GNN-based centrality approximation, while identifying closeness centrality's sensitivity to topology as an open challenge.
Samra Sana, Giorgio Mantica, Saul Imbrici
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