189 citations · 191 across the 2 of their papers we have counts for
5 papers
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang +4
The pairwise interaction paradigm of graph machine learning has predominantly governed the modelling of relational systems. However, graphs alone cannot capture the multi-level int…
Temporal Graph Networks for Deep Learning on Dynamic Graphs
Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca +3
Graph Neural Networks (GNNs) have recently become increasingly popular due to their ability to learn complex systems of relations or interactions arising in a broad spectrum of pro…
SIGN: Scalable Inception Graph Neural Networks
Fabrizio Frasca, Emanuele Rossi, Davide Eynard +3
Graph representation learning has recently been applied to a broad spectrum of problems ranging from computer graphics and chemistry to high energy physics and social media. The po…
Learning Interpretable Disease Self-Representations for Drug Repositioning
Fabrizio Frasca, Diego Galeano, Guadalupe Gonzalez +4
Drug repositioning is an attractive cost-efficient strategy for the development of treatments for human diseases. Here, we propose an interpretable model that learns disease self-r…
Fake News Detection on Social Media using Geometric Deep Learning
Federico Monti, Fabrizio Frasca, Davide Eynard +2
Social media are nowadays one of the main news sources for millions of people around the globe due to their low cost, easy access and rapid dissemination. This however comes at the…