bayesian-optimization

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

A Python implementation of global optimization with gaussian processes.

Sequential model-based optimization with a `scipy.optimize` interface

A modular active learning framework for Python

Notebooks about Bayesian methods for machine learning

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

Sequential Model-based Algorithm Configuration

a distributed Hyperband implementation on Steroids

Experimental Global Optimization Algorithm

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

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

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

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

Bayesian Optimization using GPflow

A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.

Anomaly detection for temporal data using LSTMs

A hyperparameter optimization framework, inspired by Optuna.

A lightweight framework for Gaussian processes and Bayesian optimization of black-box functions (C++-11)

Toolbox for Bayesian Optimization and Model-Based Optimization in R

Bayesian Adaptive Direct Search (BADS) optimization algorithm for model fitting in MATLAB

Surrogate Optimization Toolbox for Python

Generalized and Efficient Blackbox Optimization System [SIGKDD'21].

GPstuff - Gaussian process models for Bayesian analysis

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

Hyperparameter optimization in Julia.

A toolset for black-box hyperparameter optimisation.

A fully decentralized hyperparameter optimization framework