Learning how to explain neural networks: PatternNet and PatternAttribution

international conference on learning representations, 2018.

Cited by: 157|Bibtex|Views158
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Other Links: academic.microsoft.com|dblp.uni-trier.de|arxiv.org

Abstract:

DeConvNet, Guided BackProp, LRP, were invented to better understand deep neural networks. We show that these methods do not produce the theoretically correct explanation for a linear model. Yet they are used on multi-layer networks with millions of parameters. This is a cause for concern since linear models are simple neural networks. We ...More

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