Common machine learning algorithm implementations
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Updated
Jun 3, 2024 - C#
Common machine learning algorithm implementations
Graphics Processing Units Molecular Dynamics
GPU-accelerated NeuroEvolution of Augmenting Topologies (NEAT)
XCSF learning classifier system: rule-based online evolutionary machine learning
Flappy Bird AI (NEAT)
ES-HyperNEAT Python implementation with C++ computations for NeuroEvolution, Reinforcement Learning and VfMRI
NEAT implementation in python
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
Python implementation of the NEAT neuroevolution algorithm
CPU version of NEP
Code supplement for "Neuroevolutionary representations for learning heterogeneous treatment effects"
Evolving artificial creatures controlled by neural networks
EXONA: The Evolutionary eXploration of Neural Networks Framework -- EXACT, EXALT and EXAMM
The GOLang implementation of NeuroEvolution of Augmented Topologies (NEAT) method to evolve and train Artificial Neural Networks without error back propagation
Evolutionary Computation: A Modern Perspective ---> This is a free online book, which is actively updated now (from 2023 to 2027).
Evolutionary search for survival analysis loss function for neural networks
GPU-accelerated Evolutionary Multiobjective Optimization Using Tensorized RVEA.
Competing population model of genetically evolving neural networks
A pytorch implementation of the NEAT (NeuroEvolution of Augmenting Topologies) algorithm
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