Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6951857 | Digital Signal Processing | 2018 | 20 Pages |
Abstract
This paper provides an entry point to the problem of interpreting a deep neural network model and explaining its predictions. It is based on a tutorial given at ICASSP 2017. As a tutorial paper, the set of methods covered here is not exhaustive, but sufficiently representative to discuss a number of questions in interpretability, technical challenges, and possible applications. The second part of the tutorial focuses on the recently proposed layer-wise relevance propagation (LRP) technique, for which we provide theory, recommendations, and tricks, to make most efficient use of it on real data.
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Grégoire Montavon, Wojciech Samek, Klaus-Robert Müller,