The Partial Information Decomposition of Generative Neural Network Models

The Partial Information Decomposition of Generative Neural Network Models

In this work we study the distributed representations learnt by generative neural network models. In particular, we investigate the properties of redundant and synergistic information that groups of hidden neurons contain about the target variable. To this end, we use an emerging branch of informati...

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Bibliographic Details
Main Authors: Tycho M.S. Tax, Pedro A.M. Mediano, Murray Shanahan
Format: Article
Language:English
Published: MDPI AG 2017-09-01
Series:Entropy
Subjects:
partial information decomposition
neural networks
information theory
Online Access:https://www.mdpi.com/1099-4300/19/9/474

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