156 Open source projects that are alternatives of or similar to Bads

Python library for Bayesian hyper-parameters optimization

A modular active learning framework for Python

A C++ platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

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

Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.

Videos of deep learning optimizers moving on 3D problem-landscapes

Experimental Global Optimization Algorithm

Neural Architecture Search with Bayesian Optimisation and Optimal Transport

C++ solvers for Minimum Cost Flow Problems

Generic and efficient MATLAB solver for nonsmooth optimization problems

Visualization of various deep learning optimization algorithms using PyTorch automatic differentiation and optimizers.

a lightweight C++17 library of numerical optimization methods for nonlinear functions (Including L-BFGS-B for TensorFlow)

GPstuff - Gaussian process models for Bayesian analysis

A Python implementation of global optimization with gaussian processes.

This repository implements several swarm optimization algorithms and visualizes them. Implemented algorithms: Particle Swarm Optimization (PSO), Firefly Algorithm (FA), Cuckoo Search (CS), Ant Colony Optimization (ACO), Artificial Bee Colony (ABC), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA)

A curated list of awesome links and software libraries that are useful for robots.

Notebooks about Bayesian methods for machine learning

OptimLib: a lightweight C++ library of numerical optimization methods for nonlinear functions

Curvature Filters are efficient solvers for Variational Models

Simple, but essential Bayesian optimization package

The standard and parallel multiobjective EGO algorithms

Typesafe, purely functional Computational Intelligence

A research toolkit for particle swarm optimization in Python

AutoOED: Automated Optimal Experimental Design Platform

Implementation of Variational Quantum Factoring algorithm.

A Genetic Algorithm Framework in Python

Visualize optimization algorithms in MATLAB.

Automated Machine Learning with scikit-learn

RAVEN is a flexible and multi-purpose probabilistic risk analysis, uncertainty quantification, parameter optimization and data knowledge-discovering framework.

Sequential Model-based Algorithm Configuration

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

🎯 A comprehensive gradient-free optimization framework written in Python

Matlab and Python toolbox for fast Total Variation proximity operators

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

This mathematics course is taught for the first year Ph.D. students of computer science and related areas @ZJU

a distributed Hyperband implementation on Steroids

Algorithmic trading strategies

A header-only C++ library for numerical optimization --

[ICLR 2021] Is Attention Better Than Matrix Decomposition?

oj! Algorithms

MATLAB library for non-negative matrix factorization (NMF): Version 1.8.1

Unconstrained function minimization in Javascript

Bayesian Optimization of Combinatorial Structures

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

A toolset for black-box hyperparameter optimisation.

ytopt: machine-learning-based search methods for autotuning

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

Sequential Gallery for Interactive Visual Design Optimization [SIGGRAPH 2020]

A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

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

Neural Networks in Java 8 with CuDNN and Aparapi

DFO-GN: Derivative-Free Optimization using Gauss-Newton

BOPP: Bayesian Optimization for Probabilistic Programs

Dice.com tutorial on using black box optimization algorithms to do relevancy tuning on your Solr Search Engine Configuration from Simon Hughes Dice.com

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

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

Python microframework for building nature-inspired algorithms. Official docs: http://niapy.readthedocs.io/en/stable/

Surrogate Optimization Toolbox for Python

A fully decentralized hyperparameter optimization framework