Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Bayesian model for sparse graphs with flexible degree distribution and
  overlapping community structure   We consider a non-projective class of inhomogeneous random graph models with
interpretable parameters and a number of interesting asymptotic properties.
Using the results of Bollob\'as et al. [2007], we show that i) the class of
models is sparse and ii) depending on the choice of the parameters, the model
is either scale-free, with power-law exponent greater than 2, or with an
asymptotic degree distribution which is power-law with exponential cut-off. We
propose an extension of the model that can accommodate an overlapping community
structure. Scalable posterior inference can be performed due to the specific
choice of the link probability. We present experiments on five different
real-world networks with up to 100,000 nodes and edges, showing that the model
can provide a good fit to the degree distribution and recovers well the latent
community structure.

27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
18
The categories of this paper are: econ
2
The categories of this paper are: math
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
21
The categories of this paper are: adap-org
20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph