Boax: A Bayesian Optimization library for JAX.

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Boax: A Bayesian Optimization library for JAX.#

Note

Boax is currently in early alpha and under active development!

Boax is a composable library of core components for Bayesian Optimization that is designed for flexibility.

It comes with high-level interfaces for:

  • Experiments (boax.experiments):

    • Bayesian Optimization Setups

    • Bandit Optimization Setups

    • Search Spaces

And with low-level interfaces for:

  • Constructing acquisition functions (boax.acquisition):

    • Acquisition Functions

    • Surrogate Models

  • Constructing policy functions (boax.policies):

    • Policy Functions

    • Believes

  • Core capabilities (boax.core):

    • Common Distributions

    • Gaussian Process Models

    • Objective Functions

    • Quasi-Newton Optimizers

    • Monte-Carlo Samplers

Installation#

The latest release of Boax can be installed from PyPI using:

pip install boax

You may also install directly from GitHub, using the following command. This can be used to obtain the most recent version of Boax:

pip install git+git://github.com/Lando-L/boax.git
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