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2018 | OriginalPaper | Buchkapitel

7. Critical Challenges for the Visual Representation of Deep Neural Networks

verfasst von : Kieran Browne, Ben Swift, Henry Gardner

Erschienen in: Human and Machine Learning

Verlag: Springer International Publishing

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Abstract

Artificial neural networks have proved successful in a broad range of applications over the last decade. However, there remain significant concerns about their interpretability. Visual representation is one way researchers are attempting to make sense of these models and their behaviour. The representation of neural networks raises questions which cross disciplinary boundaries. This chapter draws on a growing collection of interdisciplinary scholarship regarding neural networks. We present six case studies in the visual representation of neural networks and examine the particular representational challenges posed by these algorithms. Finally we summarise the ideas raised in the case studies as a set of takeaways for researchers engaging in this area.

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Titel: Critical Challenges for the Visual Representation of Deep Neural Networks
verfasst von: Kieran Browne
Ben Swift
Henry Gardner
Verlag: Springer International Publishing
Buch: Human and Machine Learning
Print ISBN: 978-3-319-90402-3

Electronic ISBN: 978-3-319-90403-0

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-90403-0_7

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