2023
Don't Lie to Me! Robust and Efficient Explainability With Verified Perturbation Analysis
CVPR 2023poster
A variety of methods have been proposed to try to explain how deep neural networks make their decisions. Key to those approaches is the need to sample the pixel space efficiently in order to derive importance maps. However, it has been shown that the sampling methods used to date introduce biases an…