BayesO
BayesO: A Bayesian optimization framework in Python - Published in JOSS (2023)
piglot
piglot: an Open-source Package for Derivative-free Optimisation of Numerical Responses - Published in JOSS (2024)
approxposterior
approxposterior: Approximate Posterior Distributions in Python - Published in JOSS (2018)
PyBADS
PyBADS: Fast and robust black-box optimization in Python - Published in JOSS (2024)
smac
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
https://github.com/sparks-baird/self-driving-lab-demo
Software and instructions for setting up and running a self-driving lab (autonomous experimentation) demo using dimmable RGB LEDs, an 8-channel spectrophotometer, a microcontroller, and an adaptive design algorithm, as well as extensions to liquid- and solid-based color matching demos.
chemprop
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
metasklearn
MetaSklearn: A Metaheuristic-Powered Hyperparameter Optimization Framework for Scikit-Learn Models.
https://github.com/sparks-baird/mat_discover
A materials discovery algorithm geared towards exploring high-performance candidates in new chemical spaces.
https://github.com/aspuru-guzik-group/phoenics
Phoenics: Bayesian optimization for efficient experiment planning
https://github.com/jbrea/bayesianoptimization.jl
Bayesian optimization for Julia
https://github.com/alan-turing-institute/causal-cyber-defence
This repository contains glue-code necessary to run dynamic Causal Bayesian optimisation within the Yawning Titan cyber-simulation environment.
https://github.com/rentruewang/bocoel
Bayesian Optimization as a Coverage Tool for Evaluating LLMs. Accurate evaluation (benchmarking) that's 10 times faster with just a few lines of modular code.
https://github.com/acerbilab/amortized-conditioning-engine
Amortized Probabilistic Conditioning for Optimization, Simulation and Inference (Chang et al., AISTATS 2025)
matbench-discovery
An evaluation framework for machine learning models simulating high-throughput materials discovery.
epbo
Implementation code for the paper "Bayesian Optimization via Exact Penalty"
optimeo
OPTIMEO is a package doubled by a web application that helps you optimize your experimental process by generating a Design of Experiment, generating new experiments using Bayesian Optimization (BO), and analyzing the results of your experiments using Machine Learning models.
bayesian-optimization-1d-csnn
Source code of the paper entitled "Improving Fraud Detection with 1D-Convolutional Spiking Neural Networks through Bayesian Optimization", and presented at EPIA 2024, the 23rd International Conference on Artificial Intelligence.
cheetah-demos
Demos of Cheetah being used for various applications presented in "Cheetah: Bridging the Gap Between Machine Learning and Particle Accelerator Physics with High-Speed, Differentiable Simulations"
dawn-field-theory
A post-symbolic physics framework modeling intelligence, collapse, and emergence through entropy flow.
calisim
A toolbox for the calibration and evaluation of simulation models.
head
Supporting code for the "Autonomous retrosynthesis of gold nanoparticles via spectral shape matching" paper. DOI : 10.1039/D2DD00025C
bayesian_optimization_python
Repository for Bayesian Optimization with a small surrogate model library in Python
https://github.com/cyberagentailab/preferentialbo
(ICML2023) Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes
bayesian-optimization
An introduction to Bayesian optimization with an example of accelerator tuning task.
https://github.com/acerbilab/bads
Bayesian Adaptive Direct Search (BADS) optimization algorithm for model fitting in MATLAB
https://github.com/machinelearningnuremberg/deeprankingensembles
[ICLR 2023] Deep Ranking Ensembles for Hyperparameter Optimization
priorelicitation
Shiny application for prior elicitation experiments from "Probabilistic elicitation of expert knowledge through assessment of computer simulations"
https://github.com/cyriljl/apyxl
apyxl simplifies non-linear regressions/classifications and model explainability for all users
syne-tune
Large scale and asynchronous Hyperparameter and Architecture Optimization at your fingertips.
https://github.com/data-science-in-mechanical-engineering/hci-gibo
Code to reproduce the results from the paper "Simulation-Aided Policy Tuning for Black-Box Robot Learning".
Limbo
Limbo: A Flexible High-performance Library for Gaussian Processes modeling and Data-Efficient Optimization - Published in JOSS (2018)
emqaoa-darbo
This is the github repo to support the manuscript "Quantum approximate optimization via learning-based adaptive optimization"