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MFABA: A More Faithful and Accelerated Boundary-Based Attribution Method for Deep Neural Networks
To better understand the output of deep neural networks (DNN), attribution based methods have been an important approach for model interpretability, which assign a score for each input dimension to indicate its importance towards the model outcome. Notably, the attribution methods use the axioms of
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