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Infomax

Known as: Infomax principle 
Infomax is an optimization principle for artificial neural networks and other information processing systems. It prescribes that a function that maps… 
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Related topics

Related topics

4 relations
AlgorithmIndependent component analysisMutual information

Broader (1)

Computational neuroscience

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2020
Highly Cited
2020
InfoMax-GAN: Improved Adversarial Image Generation via Information Maximization and Contrastive Learning
While Geerative Adversarial Networks (GANs) are fundamental to many generative modelling applications, they suffer from numerous… 
2019
2019
Spatio-Temporal Deep Graph Infomax
Spatio-temporal graphs such as traffic networks or gene regulatory systems present challenges for the existing deep learning… 
Review
2010
Review
2010
An Introduction to Independent Component Analysis: InfoMax and FastICA algorithms
This paper presents an introduction to independent component analysis (ICA). Unlike principal component analysis, which is based… 
2009
2009
A Soft-Constrained Dynamic Iterative Method of Blind Source Separation
The blind source separation problem arises when one attempts to recover source signals from their linear mixtures without… 
Highly Cited
2006
Highly Cited
2006
An analysis of entropy estimators for blind source separation
Highly Cited
2005
Highly Cited
2005
Improved local learning rule for information maximization and related applications
Highly Cited
2003
Highly Cited
2003
Recognizing faces with PCA and ICA
Highly Cited
2002
Highly Cited
2002
Blind source separation using Renyi's -marginal entropies
Highly Cited
2000
Highly Cited
2000
Independent Component Analysis of Simulated ERP Data
A recently-derived algorithm for performing Independent Component Analysis (ICA) (Bell & Sejnowski, 1995) based on information… 
1995
1995
Linear redundancy reduction learning
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