Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Naming Schema for a Human Brain-Scale Neural Network   Deep neural networks have become increasingly large and sparse, allowing for
the storage of large-scale neural networks with decreased costs of storage and
computation. Storage of a neural network with as many connections as the human
brain is possible with current versions of the high-performance Apache Accumulo
database and the Distributed Dimensional Data Model (D4M) software. Neural
networks of such large scale may be of particular interest to scientists within
the human brain Connectome community. To aid in research and understanding of
artificial neural networks that parallel existing neural networks like the
brain, a naming schema can be developed to label groups of neurons in the
artificial network that parallel those in the brain. Groups of artificial
neurons are able to be specifically labeled in small regions for future study.

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The categories of this paper are: hep-th
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg
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The categories of this paper are: comp-gas
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The categories of this paper are: eess
12
The categories of this paper are: nucl-th
37
The categories of this paper are: supr-con
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The categories of this paper are: bayes-an
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The categories of this paper are: atom-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: chao-dyn
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The categories of this paper are: acc-phys
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The categories of this paper are: quant-ph
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The categories of this paper are: dg-ga