Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Applying machine learning methods to prediction problems of lattice
  observables   We discuss the prediction of critical behavior of lattice observables in
SU(2) and SU(3) gauge theories. We show that feed-forward neural network,
trained on the lattice configurations of gauge fields as input data, finds
correlations with the target observable, which is also true in the critical
region where the neural network has not been trained. We have verified that the
neural network constructs a gauge-invariant function and this property does not
change over the entire range of the parameter space.

6
The categories of this paper are: astro-ph
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
33
The categories of this paper are: plasm-ph
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci