191 citations · 536 across the 12 of their papers we have counts for
5 papers · 1 filter
Ensemble of Counterfactual Explainers
Riccardo Guidotti, Salvatore Ruggieri
In eXplainable Artificial Intelligence (XAI), several counterfactual explainers have been proposed, each focusing on some desirable properties of counterfactual instances: minimali…
Boosting Synthetic Data Generation with Effective Nonlinear Causal Discovery
Martina Cinquini, Fosca Giannotti, Riccardo Guidotti
Synthetic data generation has been widely adopted in software testing, data privacy, imbalanced learning, and artificial intelligence explanation. In all such contexts, it is cruci…
Benchmarking and Survey of Explanation Methods for Black Box Models
Francesco Bodria, Fosca Giannotti, Riccardo Guidotti +3
The widespread adoption of black-box models in Artificial Intelligence has enhanced the need for explanation methods to reveal how these obscure models reach specific decisions. Re…
Open the Black Box Data-Driven Explanation of Black Box Decision Systems
Dino Pedreschi, Fosca Giannotti, Riccardo Guidotti +4
Black box systems for automated decision making, often based on machine learning over (big) data, map a user's features into a class or a score without exposing the reasons why. Th…
Local Rule-Based Explanations of Black Box Decision Systems
Riccardo Guidotti, Anna Monreale, Salvatore Ruggieri +3
The recent years have witnessed the rise of accurate but obscure decision systems which hide the logic of their internal decision processes to the users. The lack of explanations f…