Topological Information Data Analysis
This paper presents methods that quantify the structure of statistical interactions within a given data set, and were applied in a previous article. It establishes new results on the <i>k</i>-multivariate mutual-information (<inline-formula> <math display="inline">...
Main Authors: | Pierre Baudot, Monica Tapia, Daniel Bennequin, Jean-Marc Goaillard |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-09-01
|
Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/21/9/869 |
Similar Items
-
The Poincaré-Shannon Machine: Statistical Physics and Machine Learning Aspects of Information Cohomology
by: Pierre Baudot
Published: (2019-09-01) -
Generalised Measures of Multivariate Information Content
by: Conor Finn, et al.
Published: (2020-02-01) -
Understanding Interdependency Through Complex Information Sharing
by: Fernando Rosas, et al.
Published: (2016-01-01) -
Information Decomposition and Synergy
by: Eckehard Olbrich, et al.
Published: (2015-05-01) -
Quantifying Unique Information
by: Nils Bertschinger, et al.
Published: (2014-04-01)