Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: GAM: Explainable Visual Similarity and Classification via Gradient
  Activation Maps   We present Gradient Activation Maps (GAM) - a machinery for explaining
predictions made by visual similarity and classification models. By gleaning
localized gradient and activation information from multiple network layers, GAM
offers improved visual explanations, when compared to existing alternatives.
The algorithmic advantages of GAM are explained in detail, and validated
empirically, where it is shown that GAM outperforms its alternatives across
various tasks and datasets.

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The categories of this paper are: atom-ph
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The categories of this paper are: funct-an
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The categories of this paper are: adap-org
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The categories of this paper are: chao-dyn
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The categories of this paper are: nucl-ex
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The categories of this paper are: alg-geom
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The categories of this paper are: comp-gas
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The categories of this paper are: q-fin
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The categories of this paper are: quant-ph
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The categories of this paper are: ao-sci
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The categories of this paper are: stat
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The categories of this paper are: q-bio
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The categories of this paper are: astro-ph
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The categories of this paper are: nlin
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The categories of this paper are: econ
14
The categories of this paper are: math-ph