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Found 5 papers, 2 papers with code
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit
To solve the optimization problem, we propose a new query dictionary learning algorithm inspired by classical sparse dictionary learning.
Explaining Image Classifiers with Multiscale Directional Image Representation
However, the smoothness of a mask limits its ability to separate fine-detail patterns, that are relevant for the classifier, from nearby nuisance patterns, that do not affect the classifier.
How Do Input Attributes Impact the Privacy Loss in Differential Privacy?
Differential privacy (DP) is typically formulated as a worst-case privacy guarantee over all individuals in a database.
A Rate-Distortion Framework for Explaining Black-box Model Decisions
We present the Rate-Distortion Explanation (RDE) framework, a mathematically well-founded method for explaining black-box model decisions.
Cartoon Explanations of Image Classifiers
We present CartoonX (Cartoon Explanation), a novel model-agnostic explanation method tailored towards image classifiers and based on the rate-distortion explanation (RDE) framework.
