Construct · 1 fields · 1 citations

layer-wise relevance propagation: a standalone construct

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Explainable artificial intelligence

explaining a classifier's output by redistributing it backward through the network layer by layer, producing relevance scores for each input pixel.

In explainable artificial intelligence, layer-wise relevance propagation refers to explaining a classifier's output by redistributing it backward through the network layer by layer, producing relevance scores for each input pixel. This meaning comes from Bach (2015) in PLOS ONE.[1]

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Nearby constructs

explainable artificial intelligence1 fields · 1 citationsanchor · a standalone construct intelligence6 fields · 14 citationsjingle · one name, six constructs layer3 fields · 5 citationsjingle · one word, three constructs

References

Bach, S., Binder, A., Montavon, G., Klauschen, F., Müller, K., & Samek, W. (2015). On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation. PLOS ONE, 10(7), e0130140. https://doi.org/10.1371/journal.pone.0130140

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