Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimating mutual information and multi--information in large networks   We address the practical problems of estimating the information relations
that characterize large networks. Building on methods developed for analysis of
the neural code, we show that reliable estimates of mutual information can be
obtained with manageable computational effort. The same methods allow
estimation of higher order, multi--information terms. These ideas are
illustrated by analyses of gene expression, financial markets, and consumer
preferences. In each case, information theoretic measures correlate with
independent, intuitive measures of the underlying structures in the system.

16
The categories of this paper are: stat
6
The categories of this paper are: astro-ph
3
The categories of this paper are: physics
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
30
The categories of this paper are: q-alg
32
The categories of this paper are: atom-ph
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an