most citedGCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

14 citations · 14 across the 2 of their papers we have counts for

collaborators

2 papers

cs.LG2021★ 14 cited

GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks

Lucie Charlotte Magister, Dmitry Kazhdan, Vikash Singh +1

While graph neural networks (GNNs) have been shown to perform well on graph-based data from a variety of fields, they suffer from a lack of transparency and accountability, which h…

cs.LG2021

Algorithmic Concept-based Explainable Reasoning

Dobrik Georgiev, Pietro Barbiero, Dmitry Kazhdan +2

Recent research on graph neural network (GNN) models successfully applied GNNs to classical graph algorithms and combinatorial optimisation problems. This has numerous benefits, su…