The Robustness of Counterfactual Explanations Over Time

The Robustness of Counterfactual Explanations Over Time

Counterfactual explanations are a prominent example of post-hoc interpretability methods in the explainable Artificial Intelligence (AI) research domain. Differently from other explanation methods, they offer the possibility to have recourse against unfavourable outcomes computed by machine learning...

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Bibliographic Details
Main Authors: Andrea Ferrario, Michele Loi
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Machine learning
explainable artificial intelligence
counterfactual explanations
robustness
algorithmic recourse
counterfactual data augmentation
Online Access:https://ieeexplore.ieee.org/document/9851645/

Internet

https://ieeexplore.ieee.org/document/9851645/

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