Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Toward Scalable Verification for Safety-Critical Deep Networks   The increasing use of deep neural networks for safety-critical applications,
such as autonomous driving and flight control, raises concerns about their
safety and reliability. Formal verification can address these concerns by
guaranteeing that a deep learning system operates as intended, but the state of
the art is limited to small systems. In this work-in-progress report we give an
overview of our work on mitigating this difficulty, by pursuing two
complementary directions: devising scalable verification techniques, and
identifying design choices that result in deep learning systems that are more
amenable to verification.

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The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
13
The categories of this paper are: quant-ph
10
The categories of this paper are: q-bio
20
The categories of this paper are: acc-phys
34
The categories of this paper are: chem-ph
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The categories of this paper are: nucl-ex
2
The categories of this paper are: math
33
The categories of this paper are: plasm-ph