jaxbo 0.1.2

Fork of PredictiveIntelligenceLab/JAX-BO with updates and compatibility improvements for Colab and pipelines

JAX-BO (Extended): Bayesian Optimization in JAX

This is a modified and extended version of the original JAX-BO library for Bayesian optimization, with improved compatibility and enhancements for modern Python and JAX versions.

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Getting Started

Installation

You can install the latest version from PyPI:

pip install jaxbo

Launch the interactive tutorial on Google Colab:

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Maintainer and Fork Information

This fork is maintained by Ricardo García Ramírez, as of May 2025.

Summary of Modifications

• Updated for compatibility with Python 3.12
• Migrated to recent versions of jax and jaxlib
• Fixed and tested all demo notebooks and example scripts
• Added detailed documentation to all public functions and modules
• Improved error handling and logging output
• Refactored and expanded optimizer functionality
• Clarified model design and acquisition strategy logic

Note: This fork is not affiliated with the original authors. It is maintained independently to support downstream research applications.

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Original Project

This project is based on the original JAX-BO library developed by the Predictive Intelligence Lab at the University of Pennsylvania.

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Citation (Original Work)

If you use this library in your research, please cite the original authors:

@software{jaxbo2020github,
  author = {Paris Perdikaris, Yibo Yang, Mohamed Aziz Bhouri},
  title = {{JAX-BO}: A Bayesian optimization library in {JAX}},
  url = {https://github.com/PredictiveIntelligenceLab/JAX-BO},
  version = {0.2},
  year = {2020},
}

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Changelog

All modifications and release notes are documented in the CHANGELOG file.

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License

This project is licensed under the Apache License 2.0. See the LICENSE file for details.