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Non-Negative sparse auto encoder written in pytorch

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alemme/pytorch-nnsae

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Overview

     Copyright (c) 2012 F. R. Reinhart, CoR-Lab
     Univertiy 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.

START

  1. Execute the barsExampleNNSAE.py script
  2. Execute the mnistExampleNNSAE.py script

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Non-Negative sparse auto encoder written in pytorch

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