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Python implementation of CMA-ES
The main features of cma-es/pycma are: Optimization.
Open-source alternatives to cma-es/pycma include: anyoptimization/pymoo — NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO. automl/smac3 — SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization. autonomio/talos — Hyperparameter Experiments with TensorFlow and Keras. befelix/safeopt — Safe Bayesian Optimization. claesenm/optunity — optimization routines for hyperparameter tuning. 100/solid — 🎯 A comprehensive gradient-free optimization framework written in Python.
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
Hyperparameter Experiments with TensorFlow and Keras
