Privacy-Preserving Case-Based Explanations: Enabling Visual Interpretability by Protecting Privacy
Deep Learning achieves state-of-the-art results in many domains, yet its black-box nature limits its application to real-world contexts.An intuitive way to improve the interpretability of Deep Learning models is by explaining their decisions with similar cases.However, case-based explanations cannot be used in contexts where the data exposes person