sustaining_gazes/matlab_version/face_validation/DeepLearnToolbox/README_header.md
2016-04-28 15:40:36 -04:00

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DeepLearnToolbox

A Matlab toolbox for Deep Learning.

Deep Learning is a new subfield of machine learning that focuses on learning deep hierarchical models of data. It is inspired by the human brain's apparent deep (layered, hierarchical) architecture. A good overview of the theory of Deep Learning theory is Learning Deep Architectures for AI

For a more informal introduction, see the following videos by Geoffrey Hinton and Andrew Ng.

If you use this toolbox in your research please cite Prediction as a candidate for learning deep hierarchical models of data

@MASTERSTHESIS\{IMM2012-06284,
    author       = "R. B. Palm",
    title        = "Prediction as a candidate for learning deep hierarchical models of data",
    year         = "2012",
}

Contact: rasmusbergpalm at gmail dot com

Directories included in the toolbox

NN/ - A library for Feedforward Backpropagation Neural Networks

CNN/ - A library for Convolutional Neural Networks

DBN/ - A library for Deep Belief Networks

SAE/ - A library for Stacked Auto-Encoders

CAE/ - A library for Convolutional Auto-Encoders

util/ - Utility functions used by the libraries

data/ - Data used by the examples

tests/ - unit tests to verify toolbox is working

For references on each library check REFS.md

Setup

  1. Download.
  2. addpath(genpath('DeepLearnToolbox'));

Known errors

test_cnn_gradients_are_numerically_correct fails on Octave because of a bug in Octave's convn implementation. See http://savannah.gnu.org/bugs/?39314

test_example_CNN fails in Octave for the same reason.