Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability

Roman Levin, Manli Shu, Eitan Borgnia +3

Conventional saliency maps highlight input features to which neural network predictions are highly sensitive. We take a different approach to saliency, in which we identify and ana…