The hopfield package

[Tags: library, mit, program]

Attractor Neural Networks for Modelling Associative Memory

Report: https://github.com/imperialhopfield/hopfield/raw/master/report/report.pdf

A third year group project at Imperial College London, supervised by Prof. Abbas Edalat.

This projects implements:

and comes with a range of experiments to evaluate their properties.


Properties

Versions0.1.0.0, 0.1.0.1, 0.1.0.2
Dependenciesarray (>=0.4.0.0), base (>=4 && <=5), deepseq (>=1.3.0.0), directory (>=1.1.0.2), erf (>=2.0.0.0), exact-combinatorics (>=0.2.0.4), hmatrix (>=0.11.0.4), hopfield, JuicyPixels (>=2.0.0), monad-loops (>=0.3.3.0), MonadRandom (>=0.1.8), optparse-applicative (>=0.5.0.0), parallel (>=3.1.0.1), probability (>=0.2.4), QuickCheck (>=2.4.2), random (>=1.0.1.1), random-fu (>=0.2.3.1), rvar (>=0.2.0.1), split (>=0.2.1.1), vector (>=0.9.1)
LicenseMIT
CopyrightCopyright: (c) 2012 Mihaela Rosca, Lukasz Severyn, Niklas Hambuechen, Razvan Marinescu, Wael Al Jisihi
AuthorMihaela Rosca, Lukasz Severyn, Niklas Hambuechen, Razvan Marinescu, Wael Al Jisihi
MaintainerNiklas Hambuechen <mail@nh2.me>
Stabilityexperimental
CategoryAI, Machine Learning
Home pagehttps://github.com/imperialhopfield/hopfield
Bug trackerhttps://github.com/imperialhopfield/hopfield/issues
Source repositoryhead: git clone git://github.com/imperialhopfield/hopfield.git
Executablesrecognize, experiment
UploadedThu Dec 12 10:40:31 UTC 2013 by NiklasHambuechen
Downloads332 total (24 in last 30 days)
StatusDocs uploaded by user [build log]
All reported builds failed [all 1 reports]

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