Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dimension reduction in heterogeneous neural networks: generalized
  Polynomial Chaos (gPC) and ANalysis-Of-VAriance (ANOVA)   We propose, and illustrate via a neural network example, two different
approaches to coarse-graining large heterogeneous networks. Both approaches are
inspired from, and use tools developed in, methods for uncertainty
quantification in systems with multiple uncertain parameters - in our case, the
parameters are heterogeneously distributed on the network nodes. The approach
shows promise in accelerating large scale network simulations as well as
coarse-grained fixed point, periodic solution and stability analysis. We also
demonstrate that the approach can successfully deal with structural as well as
intrinsic heterogeneities.

18
The categories of this paper are: econ
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
24
The categories of this paper are: dg-ga
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
31
The categories of this paper are: ao-sci
28
The categories of this paper are: alg-geom
0
The categories of this paper are: hep-ph
2
The categories of this paper are: math
17
The categories of this paper are: q-fin