Graph Neural Networks for Scalable and Transferable Node Centrality Approximation

Samra Sana, Giorgio Mantica, Saul Imbrici

Graph Neural Networks (GNNs) provide a learning-based framework for approximating graph quantities that are expensive to compute exactly. This paper investigates GNNs for scalable…