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Uncertainty Quantification for Gradient-based Explanations in Neural Networks
By computing the coefficient of variation of these distributions, we evaluate the confidence in the explanation and determine that the explanations generated using Guided Backpropagation have low uncertainty associated with them.
Sanity Checks for Explanation Uncertainty
Explanations for machine learning models can be hard to interpret or be wrong.
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