Bayesian Optimization Python Packages

bayesian-optimization

A Python implementation of global optimization with gaussian processes.

google-vizier

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

emukit

A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc.

nni

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

arm-mango

Parallel Hyperparameter Tuning in Python

smac

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

gradient-free-optimizers

Lightweight optimization with local, global, population-based and sequential techniques across mixed search spaces

matbench-discovery

An evaluation framework for machine learning models simulating high-throughput materials discovery.

tune-sklearn

A drop-in replacement for Scikit-Learn’s GridSearchCV / RandomizedSearchCV -- but with cutting edge hyperparameter tuning techniques.

google-vizier-dev

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

baybe

Bayesian Optimization and Design of Experiments

bofire

Experimental design and (multi-objective) bayesian optimization.

hpbandster

a distributed Hyperband implementation on Steroids

hyperactive

A unified interface for optimization algorithms and experiments

pysot

Surrogate Optimization Toolbox for Python

sambo

🎯 📈 Sequential and Model-Based Optimization in Python, feat. SCE-UA, SMBO & SHGO. SOTA perf; 0 deps

pybads

PyBADS: Bayesian Adaptive Direct Search optimization algorithm for model fitting in Python

chekipeuq

Parameter estimation for complex physical problems often suffers from finding ‘solutions’ that are not physically realistic. The PEUQSE software provides tools for finding physically realistic parameter estimates, graphs of the parameter estimate positions within parameter space, and plots of the final simulation results.

bayes-optim

Bayesian Optimization algorithms with various recent improvements

syne-tune

Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.

bayesmark

Benchmark framework to easily compare Bayesian optimization methods on real machine learning tasks

bask

A fully Bayesian implementation of sequential model-based optimization

physbo

PHYSBO -- optimization tools for PHYsics based on Bayesian Optimization

octis

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)