2 papers
cs.AI2026
Evaluating Counterfactual Explanation Methods on Incomplete Inputs
Francesco Leofante, Daniel Neider, Mustafa Yalçıner
Existing algorithms for generating Counterfactual Explanations (CXs) for Machine Learning (ML) typically assume fully specified inputs. However, real-world data often contains miss…
cs.CY2024
Explainable AI: Definition and attributes of a good explanation for health AI
Evangelia Kyrimi, Scott McLachlan, Jared M Wohlgemut +4
Proposals of artificial intelligence (AI) solutions based on increasingly complex and accurate predictive models are becoming ubiquitous across many disciplines. As the complexity…