Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Colored Noise Injection for Training Adversarially Robust Neural
  Networks   Even though deep learning has shown unmatched performance on various tasks,
neural networks have been shown to be vulnerable to small adversarial
perturbations of the input that lead to significant performance degradation. In
this work we extend the idea of adding white Gaussian noise to the network
weights and activations during adversarial training (PNI) to the injection of
colored noise for defense against common white-box and black-box attacks. We
show that our approach outperforms PNI and various previous approaches in terms
of adversarial accuracy on CIFAR-10 and CIFAR-100 datasets. In addition, we
provide an extensive ablation study of the proposed method justifying the
chosen configurations.

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The categories of this paper are: atom-ph
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The categories of this paper are: chem-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: nucl-th
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The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
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The categories of this paper are: nucl-ex
31
The categories of this paper are: ao-sci
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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: econ
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The categories of this paper are: hep-lat
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The categories of this paper are: q-bio
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The categories of this paper are: cmp-lg
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The categories of this paper are: funct-an
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The categories of this paper are: astro-ph