bayex
A lightweight Bayesian optimization library built on JAX for efficient optimization of expensive-to-evaluate functions.
What is bayex?
Bayex is a lightweight Bayesian optimization library built on JAX for efficiently optimizing expensive-to-evaluate functions. It uses Gaussian Process models and acquisition functions to guide the search for optimal parameters in domains like hyperparameter tuning and experimental design.
Machine learning practitioners and researchers who need to optimize costly black-box functions, particularly those already working with JAX for high-performance computing.
Developers choose Bayex for its minimal design, JAX-powered performance, and straightforward API, offering a focused alternative to heavier Bayesian optimization libraries.
Overview
Minimal Implementation of Bayesian Optimization in JAX
Use Cases
Best For
- Hyperparameter tuning for machine learning models
- Optimizing expensive simulation-based objective functions
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