2023
Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees
ICML 2023poster
There is an emerging interest in generating robust counterfactual explanations that would remain valid if the model is updated or changed even slightly. Towards finding robust counterfactuals, existing literature often assumes that the original model $m$ and the new model $M$ are bounded in the para…