counterfactual

A Survey on Graph Counterfactual Explanations: Definitions, Methods, Evaluation, and Research Challenges
Graph Neural Networks (GNNs) perform well in community detection and molecule classification. Counterfactual Explanations (CE) provide …
Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo, Fosca Giannotti
PDF Cite Code DOI
Adapting to Change: Robust Counterfactual Explanations in Dynamic Data Landscapes
We introduce a novel semi-supervised Graph Counterfactual Explainer (GCE) methodology, Dynamic GRAph Counterfactual Explainer …
Bardh Prenkaj, Mario Villaizan-Vallelado, Tobias Leemann, Gjergji Kasneci
PDF Cite Code Poster Slides DOI
Developing and Evaluating Graph Counterfactual Explanation with GRETEL
The black-box nature and the lack of interpretability detract from constant improvements in Graph Neural Networks (GNNs) performance in …
Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo
PDF Cite Code DOI
Ensemble approaches for Graph Counterfactual Explanations
In recent years, Graph Neural Networks have reported outstanding performances in tasks like community detection, molecule …
Mario Alfonso Prado-Romero, Bardh Prenkaj, Giovanni Stilo, Alessandro Celi, Ernesto Estevanell-Valladares, Daniel Alejandro Valdés-Pérez
Cite Code
Ensemble approaches for Graph Counterfactual Explanations