simple-genetic-algorithm-mr VS tensor-safe

Compare simple-genetic-algorithm-mr vs tensor-safe and see what are their differences.

simple-genetic-algorithm-mr

Fork of simple-genetic-algorithm using MonadRandom (by JPMoresmau)

tensor-safe

A Haskell framework to define valid deep learning models and export them to other frameworks like TensorFlow JS or Keras. (by leopiney)
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simple-genetic-algorithm-mr tensor-safe
- -
2 101
- -
0.0 0.0
about 9 years ago almost 2 years ago
Haskell Haskell
BSD 3-clause "New" or "Revised" License BSD 3-clause "New" or "Revised" License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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simple-genetic-algorithm-mr

Posts with mentions or reviews of simple-genetic-algorithm-mr. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning simple-genetic-algorithm-mr yet.
Tracking mentions began in Dec 2020.

tensor-safe

Posts with mentions or reviews of tensor-safe. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning tensor-safe yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing simple-genetic-algorithm-mr and tensor-safe you can also consider the following projects:

simple-genetic-algorithm - Simple parallel genetic algorithm implementation in pure Haskell

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.

hnn - haskell neural network library

hasktorch - Tensors and neural networks in Haskell

Etage - A general data-flow framework featuring nondeterminism, laziness and neurological pseudo-terminology.

opencv - Haskell binding to OpenCV-3.x

simple-neural-networks - Simple parallel neural networks implementation in pure Haskell

HSGEP - Haskell Gene Expression Programming Library

liblinear-enumerator - Haskell bindings to liblinear

cv-combinators - Functional Combinators for Computer Vision, currently using OpenCV as a backend

neet - Neuroevolution of Augmented Topologies (NEAT) -- in Haskell

GA - Haskell module for working with genetic algorithms

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