3 papers
cs.LG2023
Viewing the process of generating counterfactuals as a source of knowledge: a new approach for explaining classifiers
Vincent Lemaire, Nathan Le Boudec, Victor Guyomard +1
There are now many explainable AI methods for understanding the decisions of a machine learning model. Among these are those based on counterfactual reasoning, which involve simula…
cs.LG2023
Generating robust counterfactual explanations
Victor Guyomard, Françoise Fessant, Thomas Guyet +2
Counterfactual explanations have become a mainstay of the XAI field. This particularly intuitive statement allows the user to understand what small but necessary changes would have…
cs.AI2022
VCNet: A self-explaining model for realistic counterfactual generation
Victor Guyomard, Françoise Fessant, Thomas Guyet +2
Counterfactual explanation is a common class of methods to make local explanations of machine learning decisions. For a given instance, these methods aim to find the smallest modif…