49 citations · 144 across the 24 of their papers we have counts for
4 papers · 2 filters
A Self-Explainable Heterogeneous GNN for Relational Deep Learning
Francesco Ferrini, Antonio Longa, Andrea Passerini +1
Recently, significant attention has been given to the idea of viewing relational databases as heterogeneous graphs, enabling the application of graph neural network (GNN) technolog…
xAI-Drop: Don't Use What You Cannot Explain
Vincenzo Marco De Luca, Antonio Longa, Pietro Liò +1
Graph Neural Networks (GNNs) have emerged as the predominant paradigm for learning from graph-structured data, offering a wide range of applications from social network analysis to…
Analysing the Behaviour of Tree-Based Neural Networks in Regression Tasks
Peter Samoaa, Mehrdad Farahani, Antonio Longa +2
The landscape of deep learning has vastly expanded the frontiers of source code analysis, particularly through the utilization of structural representations such as Abstract Syntax…
Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs
Steve Azzolin, Antonio Longa, Stefano Teso +1
As Graph Neural Networks (GNNs) become more pervasive, it becomes paramount to build reliable tools for explaining their predictions. A core desideratum is that explanations are \t…