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cs.LG2023
Combining Stochastic Explainers and Subgraph Neural Networks can Increase Expressivity and Interpretability
Indro Spinelli, Michele Guerra, Filippo Maria Bianchi +1
Subgraph-enhanced graph neural networks (SGNN) can increase the expressive power of the standard message-passing framework. This model family represents each graph as a collection…
cs.LG2023
Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networks
Indro Spinelli, Riccardo Bianchini, Simone Scardapane
The rise of graph representation learning as the primary solution for many different network science tasks led to a surge of interest in the fairness of this family of methods. Lin…