Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Efficient variational Bayesian neural network ensembles for outlier
  detection   In this work we perform outlier detection using ensembles of neural networks
obtained by variational approximation of the posterior in a Bayesian neural
network setting. The variational parameters are obtained by sampling from the
true posterior by gradient descent. We show our outlier detection results are
comparable to those obtained using other efficient ensembling methods.

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The categories of this paper are: astro-ph
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The categories of this paper are: math-ph
31
The categories of this paper are: ao-sci
13
The categories of this paper are: quant-ph
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The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
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The categories of this paper are: nlin
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The categories of this paper are: gr-qc
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The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
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The categories of this paper are: chao-dyn
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The categories of this paper are: alg-geom
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The categories of this paper are: bayes-an
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The categories of this paper are: math
8
The categories of this paper are: hep-ex
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The categories of this paper are: hep-lat