There are 2 repositories under gradient-free-optimization topic.
Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.
PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially their *Large-Scale* versions/variants (evolutionary algorithms/swarm-based optimizers/pattern search/...). [https://pypop.rtfd.io/]
Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.
Gradient-free optimization method for multivariable functions based on the low rank tensor train (TT) format and maximal-volume principle.
Gradient-free optimization method for the multidimensional arrays and discretized multivariate functions based on the tensor train (TT) format.
Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.
Deep Neural Network Optimization Platform with Gradient-based, Gradient-Free Algorithms
Markov Chain Monte Carlo binary network optimization
🥭 MANGO: Maximization of neural Activation via Non-Gradient Optimization
Gradient free reinforcement learning for PyTorch
EvoRBF: Evolving Radial Basis Function Network by Intelligent Nature-inspired Algorithms
Black-box adversarial attacks on deep neural networks with tensor train (TT) decomposition and PROTES optimizer.
Particle Swarm Optimiser
Zeroth order Frank Wolfe algorithm. Project for the Optimization for Data Science exam.
Gradient Free Reinforcement Learning solving Openai gym LunarLanderV2 by Evolution Strategy (Genetic Algorithm)
A pure-MATLAB library of EVolutionary (population-based) OPTimization for Large-Scale black-box continuous Optimization (evopt-lso).
Sparse Perturbations for Improved Convergence in Stochastic Zeroth-Order Optimization
Exploring evolutionary protein fitness landscapes
A Julia implementation of Simultaneous Perturbation Stochastic Approximation
A pure-MATLAB library for POPulation-based Large-Scale Black-Box Optimization (pop-lsbbo).
A collection and visualization of single objective black-box functions for optimization benchmarking.
Implementation of smoothing-based optimization algorithms
fireworks swarm optimization - efficient derivative free solver.
Implementation code for the paper "Bayesian Optimization via Exact Penalty"
PRIMA: Reference Implementation for Powell's methods with Modernization and Amelioration
Gradient-free online optimization loosely based on Adaptive Moment Estimation (Adam)
ESKit is a portable library written in C, that provides implementations of some self-adaptive evolution strategies
Snake RL - Reinforcement Learning that solves the Snake game. RL was implemented by Gradient-Free-Optimizers library available for Python, neural networks was created in Keras and game was created in Pygame.
Snake SL - Supervised Learning that solves the Snake game. SL was implemented by Gradient-Free-Optimizers library available for Python, neural networks was created in Keras and game was created in Pygame.
a minimal implementation of the random search algorithm for reinforcement learning.
Numerical optimization via mollifier smoothing
Particle Swarm Optimisation, Genetic Algorithm/Programming for (Gradient-Free) Neural Network Optimisation