EGObox🔗

Rust toolbox for Efficient Global Optimization method (arguably the most well-known bayesian optimization algorithm) which adresses the gradient-free optimization of expensive objective functions.

EGObox is twofold:

1. for end-users: a Python module, the Python binding of the optimizer named Egor and the surrogate model Gpx, mixture of Gaussian processes, written in Rust.
2. for developers: a set of Rust crates useful to use or implement bayesian optimization (EGO-like) algorithms.

Content🔗

This website focuses on Python interface and contains the following sections:

• Get started: learn to install EGObox
• Examples: discover usage of EGObox
• Tutorials: interactive tutorials to learn how to use EGObox
• Cookbook: find practical recipes for Egor optimizer common tasks
• Python API: reference for the Python interface

Cite🔗

The EGObox toolbox rationale is described in the JOSS paper:

@article{
  Lafage2022, 
  author = {Rémi Lafage}, 
  title = {EGObox, a Rust toolbox for efficient global optimization}, 
  journal = {Journal of Open Source Software} 
  year = {2022}, 
  doi = {10.21105/joss.04737}, 
  url = {https://doi.org/10.21105/joss.04737}, 
  publisher = {The Open Journal}, 
  volume = {7}, 
  number = {78}, 
  pages = {4737}, 
}