Search Packages

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.

arm-mango

Parallel Hyperparameter Tuning in Python

nni

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

matbench-discovery

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

smac

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

google-vizier

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

hpbandster

a distributed Hyperband implementation on Steroids

tune-sklearn

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

gradient-free-optimizers

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

baybe

Bayesian Optimization and Design of Experiments

hyperactive

A unified interface for optimization algorithms and experiments

google-vizier-dev

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

syne-tune

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

bofire

Experimental design and (multi-objective) bayesian optimization.

pysot

Surrogate Optimization Toolbox for 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.

mopti

Lightweight tools for experimental design and multi-objective optimization.

flowboost

🏄‍♂️ Multi-objective optimization library for OpenFOAM, powered by Ax. Modular, optimizer-agnostic, cluster-native.

sambo

🎯 📈 Sequential and Model-Based Optimization in Python, featuring SCE-UA, SMBO, and SHGO algorithms. SOTA perfomance; 0 deps.

bayes-optim

Bayesian Optimization algorithms with various recent improvements

entmoot

Multiobjective black-box optimization using gradient-boosted trees

octis

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

calisim

A toolbox for the calibration and evaluation of simulation models.

bask

A fully Bayesian implementation of sequential model-based optimization