Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: deepstruct -- linking deep learning and graph theory   deepstruct connects deep learning models and graph theory such that different
graph structures can be imposed on neural networks or graph structures can be
extracted from trained neural network models. For this, deepstruct provides
deep neural network models with different restrictions which can be created
based on an initial graph. Further, tools to extract graph structures from
trained models are available. This step of extracting graphs can be
computationally expensive even for models of just a few dozen thousand
parameters and poses a challenging problem. deepstruct supports research in
pruning, neural architecture search, automated network design and structure
analysis of neural networks.

25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
31
The categories of this paper are: ao-sci
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
33
The categories of this paper are: plasm-ph
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex