Separable explanations of neural network decisions

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Deep Taylor Decomposition is a method used to explain neural network decisions.
When applying this method to non-dominant classifications, the resulting explanation does not reflect important features for the chosen classification. We propose that this is caused by the dense layers and propose a method to alleviate the effect by applying regularization. We assess the result by measuring the quality of the resulting explanations objectively and subjectively.
Original languageEnglish
Title of host publicationProceedings of the 31st Conference on Neural Information Processing Systems (NIPS 2017)
Number of pages8
Publication date2017
Publication statusPublished - 2017
Event31st Conference on Neural Information Processing Systems - Long Beach, United States
Duration: 4 Dec 20179 Dec 2017

Conference

Conference31st Conference on Neural Information Processing Systems
CountryUnited States
CityLong Beach
Period04/12/201709/12/2017

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