2 citations · 2 across the 1 of their papers we have counts for
3 papers
Graph Rewiring in GNNs to Mitigate Over-Squashing and Over-Smoothing: A Survey
Hugo Attali, Nathalie Pernelle, Davide Buscaldi +1
Graph Neural Networks are powerful models for learning from graph-structured data, yet their effectiveness is often limited by two critical challenges: over-squashing, where inform…
Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks
Hugo Attali, Thomas Papastergiou, Nathalie Pernelle +1
Graph Neural Networks (GNNs) have emerged as the leading paradigm for learning over graph-structured data. However, their performance is limited by issues inherent to graph topolog…
Graph Rewiring in GNNs to Mitigate Over-Squashing and Over-Smoothing: A Survey
Hugo Attali, Davide Buscaldi, Nathalie Pernelle +1
Graph Neural Networks are powerful models for learning from graph-structured data, yet their effectiveness is often limited by two critical challenges: over-squashing, where inform…