GNN-LoFI: A novel graph neural network through localized feature-based histogram intersection

Alessandro Bicciato, Luca Cosmo, Giorgia Minello, Luca Rossi, Andrea Torsello

Abstract: Highlights•We propose a novel GNN that analyzes local distributions of node features.•These are compared against learned ones using the histogram intersection kernel.•The similarity information is propagated to other nodes in the network.•This creates a message passing mechanism where the aggregation is non-linear.•Extensive experimental results demonstrate the competitiveness of our model.