Publications
Conference
Jiang J, Leofante F, Rago A, et al., Formalising the robustness of counterfactual explanations for neural networks, The 37th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence
Albini E, Rago A, Baroni P, et al., Descriptive accuracy in explanations: the case of probabilistic classifiers, 15th International Conference on Scalable Uncertainty Management (SUM 2022)
Sukpanichnant P, Rago A, Lertvittayakumjorn P, et al., 2022, Neural QBAFs: explaining neural networks under LRP-based argumentation frameworks, International Conference of the Italian Association for Artificial Intelligence, Springer International Publishing, Pages:429-444, ISSN:0302-9743
Jiang J, Rago A, Toni F, Should counterfactual explanations always be data instances?, XLoKR 2022: The Third Workshop on Explainable Logic-Based Knowledge Representation
Irwin B, Rago A, Toni F, 2022, Argumentative forecasting, AAMAS 2022, ACM, Pages:1636-1638