MUPAX's feature importance is a weighted average of masked inputs selected for low loss, and its accuracy gains stem from using ground-truth labels during mask selection.
Deep learning methods for anatomical landmark detection in video capsule endoscopy images
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MUPAX: Multidimensional Problem Agnostic eXplainable AI
MUPAX's feature importance is a weighted average of masked inputs selected for low loss, and its accuracy gains stem from using ground-truth labels during mask selection.