Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Empowering Differential Networks Using Bayesian Analysis   Differential networks (DN) are important tools for modeling the changes in
conditional dependencies between multiple samples. A Bayesian approach for
estimating DNs, from the classical viewpoint, is introduced with a
computationally efficient threshold selection for graphical model
determination. The algorithm separately estimates the precision matrices of the
DN using the Bayesian adaptive graphical lasso procedure. Synthetic experiments
illustrate that the Bayesian DN performs exceptionally well in numerical
accuracy and graphical structure determination in comparison to
state-of-the-art methods. The proposed method is applied to South African
COVID-$19$ data to investigate the change in DN structure between various
phases of the pandemic.

27
The categories of this paper are: comp-gas
20
The categories of this paper are: acc-phys
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
32
The categories of this paper are: atom-ph
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
33
The categories of this paper are: plasm-ph
12
The categories of this paper are: nucl-th