hopfield alternatives and similar packages
Based on the "AI" category.
Alternatively, view hopfield alternatives based on common mentions on social networks and blogs.
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tensor-safe
A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras. -
moo
Genetic algorithm library for Haskell. Binary and continuous (real-coded) GAs. Binary GAs: binary and Gray encoding; point mutation; one-point, two-point, and uniform crossover. Continuous GAs: Gaussian mutation; BLX-α, UNDX, and SBX crossover. Selection operators: roulette, tournament, and stochastic universal sampling (SUS); with optional niching, ranking, and scaling. Replacement strategies: generational with elitism and steady state. Constrained optimization: random constrained initialization, death penalty, constrained selection without a penalty function. Multi-objective optimization: NSGA-II and constrained NSGA-II. -
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creatur
Framework for artificial life and other evolutionary algorithms. -
simple-genetic-algorithm
Simple parallel genetic algorithm implementation in pure Haskell -
cv-combinators
Functional Combinators for Computer Vision, currently using OpenCV as a backend -
simple-neural-networks
Simple parallel neural networks implementation in pure Haskell -
HaVSA
HaVSA (Have-Saa) is a Haskell implementation of the Version Space Algebra Machine Learning technique described by Tessa Lau. -
fei-nn
High level APIs for leaveraging neural networks with MXNet in Haskell -
hmep
Haskell Multi Expression Programming implemented with the focus on speed -
CarneadesDSL
An implementation and DSL for the Carneades argumentation model. -
Etage
A general data-flow framework featuring nondeterminism, laziness and neurological pseudo-terminology. -
simple-genetic-algorithm-mr
Fork of simple-genetic-algorithm using MonadRandom -
attoparsec-arff
An attoparsec-based parser for ARFF files in Haskell
Static code analysis for 29 languages.
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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Popular Comparisons
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hopfieldvshnn
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hopfieldvsmxnet-nn
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README
Attractor Neural Networks for Modelling Associative Memory
A third year Computing group project at Imperial College London, supervised by Prof. Abbas Edalat.
Get it from Hackage via: cabal install hopfield.
Our report: https://github.com/imperialhopfield/hopfield/raw/master/report/report.pdf
Features
This project implements (in Haskell):
- [Hopfield Networks](src/Hopfield/Hopfield.hs)
- [Clusters](src/Hopfield/Clusters.hs) and [Super Attractors](src/Hopfield/SuperAttractors.hs)
- The [Restricted Boltzmann Machine](src/Hopfield/Boltzmann/RestrictedBoltzmannMachine.hs)
- A [Boltzmann Machine for classification](src/Hopfield/Boltzmann/ClassificationBoltzmannMachine.hs)
and comes with a range of experiments to evaluate their properties.
License
MIT licensed. We appreciate a mention if our code or results were useful for you.
Written by:
- Mihaela Rosca
- Wael Al Jisihi
- Niklas Hambüchen
- Razvan Marinescu
- Lukasz Severyn
*Note that all licence references and agreements mentioned in the hopfield README section above
are relevant to that project's source code only.