126 Open source projects that are alternatives of or similar to open-box

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

The standard and parallel multiobjective EGO algorithms

Parallel Hyperparameter Tuning in Python

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

Large scale and asynchronous Hyperparameter Optimization at your fingertip.

This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"

Powell's Derivative-Free Optimization solvers

Automated Machine Learning with scikit-learn

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

Implementation of the (beetle antennae search) BAS algorithm and its mutations in R code

High-performance metaheuristics for optimization coded purely in Julia.

Sequential Model-based Algorithm Configuration

Bayesian Optimization and Grid Search for xgboost/lightgbm

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Black box hyperparameter optimization made easy.

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

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

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

Distribution transparent Machine Learning experiments on Apache Spark

Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

Anomaly detection for temporal data using LSTMs

A SciPy compatible super fast Python implementation for Particle Swarm Optimization.

Toolbox for Bayesian Optimization and Model-Based Optimization in R

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

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

Python implementation of the genetic algorithm MAP-Elites with applications in constrained optimization

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

Evolutionary Pac-Man bots using Grammatical Evolution and Multi-objective Optimization. Cool GUI included (Undergraduate Thesis)

Surrogate Optimization Toolbox for Python

Decentralized hyperparameter optimization framework, inspired by Optuna.

A Python package for approximate Bayesian inference and optimization using Gaussian processes

A toolset for black-box hyperparameter optimisation.

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

MATLAB Tool for Multi-Objective Optimization

A fully decentralized hyperparameter optimization framework

BOPP: Bayesian Optimization for Probabilistic Programs

A framework for Big Data Optimization with multi-objective metaheuristics

GPstuff - Gaussian process models for Bayesian analysis

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

【数据科学家系列课程】

A Python Library for modeling combinatorial constrained problems

Notebooks about Bayesian methods for machine learning

Multi-Objective GP for Automated Repair of Java

A modular active learning framework for Python

Bayesian Optimization of Combinatorial Structures

A curated list of awesome multi-objective optimization research resources.

Simple, but essential Bayesian optimization package

This repository contains the source code for “Thompson sampling efficient multiobjective optimization” (TSEMO).

Modern Fortran Edition of the SLSQP Optimizer

Deep learning toolkit for Drug Design with Pareto-based Multi-Objective optimization in Polypharmacology

Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

Modular Java framework for meta-heuristic optimization

pyrff: Python implementation of random fourier feature approximations for gaussian processes

Solver of multiobjective linear optimization problems (MOMIP, MOLP, MOIP, MOCO): generic part

A Python implementation of global optimization with gaussian processes.

a distributed Hyperband implementation on Steroids

A Universal Deep Reinforcement Learning Framework

Experimental Global Optimization Algorithm