On the Feasibility of Fidelity$^-$ for Graph Pruning

As one of popular quantitative metrics to assess the quality of explanation of graph neural networks (GNNs), fidelity measures the output difference after removing unimportant parts of the input graph. Fidelity has been widely used due to its straightforward interpretation that the underlying model...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Shin, Yong-Min, Shin, Won-Yong
Format:	Artikel
Sprache:	eng
Schlagworte:	Computer Science - Artificial Intelligence Computer Science - Information Theory Computer Science - Learning Computer Science - Neural and Evolutionary Computing Computer Science - Social and Information Networks Mathematics - Information Theory
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!