2020
Learning Global Transparent Models consistent with Local Contrastive Explanations
NeurIPS 2020poster
There is a rich and growing literature on producing local contrastive/counterfactual explanations for black-box models (e.g. neural networks). In these methods, for an input, an explanation is in the form of a contrast point differing in very few features from the original input and lying in a diffe…