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Found 4 papers, 1 papers with code
Fixing confirmation bias in feature attribution methods via semantic match
Feature attribution methods have become a staple method to disentangle the complex behavior of black box models.
Finding Regions of Counterfactual Explanations via Robust Optimization
To this end, our method provides a whole region of CEs allowing the user to choose a suitable recourse to obtain a desired outcome.
Semantic match: Debugging feature attribution methods in XAI for healthcare
Despite valid concerns, we argue that existing criticism on the viability of post-hoc local explainability methods throws away the baby with the bathwater by generalizing a problem that is specific to image data.
Explainable Artificial Intelligence (XAI)
Feature Importance
+1
Why we do need Explainable AI for Healthcare
The recent spike in certified Artificial Intelligence (AI) tools for healthcare has renewed the debate around adoption of this technology.
