3 citations · 3 across the 2 of their papers we have counts for
3 papers
FCx: An algorithm for finding Feasible Counterfactual Explanations
Kleopatra Markou, Vana Kalogeraki, Dimitrios Gunopulos
Counterfactual (CF) explanations identify changes that alter an input's classification. While existing methods produce realistic and low-cost CFs, they often fail to ensure feasibi…
GLANCE: Global Actions in a Nutshell for Counterfactual Explainability
Loukas Kavouras, Eleni Psaroudaki, Konstantinos Tsopelas +9
The widespread deployment of machine learning systems in critical real-world decision-making applications has highlighted the urgent need for counterfactual explainability methods…
A Framework for Feasible Counterfactual Exploration incorporating Causality, Sparsity and Density
Kleopatra Markou, Dimitrios Tomaras, Vana Kalogeraki +1
The imminent need to interpret the output of a Machine Learning model with counterfactual (CF) explanations - via small perturbations to the input - has been notable in the researc…