A new explanation method for ReLU neural networks that builds piecewise linear models from selected connected subsets of hidden units, called paths, to produce adjustable and decomposable input attributions.
Peeking inside the black-box: a survey on explainable artificial intelligence ( XAI )
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Pathwise Explanation of ReLU Neural Networks
A new explanation method for ReLU neural networks that builds piecewise linear models from selected connected subsets of hidden units, called paths, to produce adjustable and decomposable input attributions.