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Category: Conditional Restricted Boltzmann Machine

3 September 2016Conditional Restricted Boltzmann Machine, Machine Learning, Neural nets

Possible Addition of NARX Network to Conditional Restricted Boltzmann Machine

It has been over three months since my last post, due to working away from home for some of the summer, a […]

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3 February 2016C++, Conditional Restricted Boltzmann Machine, Feature extraction, Machine Learning, Neural nets, Octave, RBM

Refactored Denoising Autoencoder Update #2

Below is this second code update. % select rolling window length to use – an optimisable parameter via pso? rolling_window_length = 50 […]

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21 January 2016Conditional Restricted Boltzmann Machine, Machine Learning, Octave, RBM

Refactored Denoising Autoencoder Code Update

This code box contains updated code from my previous post. The main change is the inclusion of bias units for the directed […]

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18 January 2016Conditional Restricted Boltzmann Machine, Machine Learning, Octave, RBM

Refactored Denoising Autoencoder Code

It has been quite a challenge but I now have a working first attempt at Octave code for autoencoder pre-training of weights for […]

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24 September 2015Conditional Restricted Boltzmann Machine, Feature extraction, Particle Swarm Optimisation

Runge-Kutta Methods

As stated in my previous post I have been focusing on getting some meaningful features as possible inputs to my machine learning […]

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