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cs.LG2021★ 7 cited
Consistent Counterfactuals for Deep Models
Emily Black, Zifan Wang, Matt Fredrikson +1
Counterfactual examples are one of the most commonly-cited methods for explaining the predictions of machine learning models in key areas such as finance and medical diagnosis. Cou…
cs.LG2021★ 6 cited
Robust Models Are More Interpretable Because Attributions Look Normal
Zifan Wang, Matt Fredrikson, Anupam Datta
Recent work has found that adversarially-robust deep networks used for image classification are more interpretable: their feature attributions tend to be sharper, and are more conc…