Skip to content

TensorFlow implementations of a Restricted Boltzmann Machine and an unsupervised Deep Belief Network, including unsupervised fine-tuning of the Deep Belief Network.

License

Notifications You must be signed in to change notification settings

AnnikaLindh/DBNTensorFlow

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

6 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

DBNTensorFlow - a Deep Belief Network implementation with TensorFlow

Copyright (c) 2016 Annika Lindh
Licensed under GPLv3, see LICENSE.txt

Implementations of a Restricted Boltzmann Machine and an unsupervised Deep Belief Network, including unsupervised fine-tuning of the Deep Belief Network.

Publications

This code was used for two scientific publications. (Yes, they have the same name. Lesson learned. :P)

Requirements:

  • Python 2.7
  • tensorflow 0.8
  • NumPy 1.11.0
  • SciPy 0.13.3

The implementations have only been tested on Ubuntu but should work on any OS that you can get TensorFlow running on.


This was my first encounter with TensorFlow, so I started out from Gabriele Angeletti's Deep-Learning-TensorFlow project which has implementations for a bunch of different Deep Learning techniques. I highly recommend a look at his GitHub repo! (If you were looking for a supervised DBN, you will find that in his repo, while my implementation is of an unsupervised DBN.)

The data used for this project was extracted from the multi-wavelength FITS image data from the Sloan Digital Sky Survey database, Data Release 12. Please see the publications for more details on the data selection and preprocessing.

Feel free to use this code for your own projects or for your personal learning, but I leave no guarantees of correctness or suitability in any way. Please see the LICENSE.txt document for the terms of this software. And I'd be happy if you give me credit in any projects and/or publications. :)

Bug reports and pull requests are welcome, though I may or may not have time to look at them.
You can reach the author at code.annikalindh (at) gmail.com

About

TensorFlow implementations of a Restricted Boltzmann Machine and an unsupervised Deep Belief Network, including unsupervised fine-tuning of the Deep Belief Network.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages