Skip to content
/ NNSAE Public

Non Negative Sparse AutoEncoder (NNSAE). An efficient online learning scheme for non-negative and sparse coding in autoencoder neural networks.

Notifications You must be signed in to change notification settings

alemme/NNSAE

Repository files navigation

Overview

     Copyright (c) 2012 F. R. Reinhart, CoR-Lab
     University Bielefeld, Germany, http://cor-lab.de

The program is free for non-commercial and academic use. Please contact the author if you are interested in using the software for commercial purposes. The software must not be modified or distributed without prior permission of the authors. Please acknowledge the authors in any academic publications that have made use of this code or part of it. Please use this BibTex for reference:

A. Lemme, R. F. Reinhart and J. J. Steil. 
"Online learning and generalization of parts-based image representations 
 by Non-Negative Sparse Autoencoders". Neural Networks, vol. 33, pp. 194-203, 2012
 doi = "https://doi.org/10.1016/j.neunet.2012.05.003"
                          OR
A. Lemme, R. F. Reinhart and J. J. Steil. "Efficient online learning of
a non-negative sparse autoencoder". In Proc. ESANN, 2010.

Please send your feedbacks or questions to:

felix.reinhart_at_gmail.com
alemme01_at_t-online.de

About

Non Negative Sparse AutoEncoder (NNSAE). An efficient online learning scheme for non-negative and sparse coding in autoencoder neural networks.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published