decijax

decijax is an early-stage library which aims to provide algorithms for a variety of sequential decision-making problems. It currently provides implementations of several acquisition functions for Bayesian optimisation, including probability of improvement, expected improvement and Thompson sampling. The implementations are built upon the JAX library, enabling automatic differentiation, vectorisation, and just-in-time (JIT) compilation for high performance. This allows for efficient research, development, and deployment of decision-making agents.

⚠️ Warning

decijax is currently under active development, and the API is likely to change in the near future.

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Table of Contents

• decijax
  • Table of Contents
  • Installation
  • Documentation
  • Contributing
  • License

Installation

decijax requires Python 3.11 or later. Install the latest release from PyPI with:

pip install decijax

Documentation

Available at https://thomas-christie.github.io/decijax/.

Contributing

Please refer to the contributing guidelines file for guidelines on how to contribute to the project.

License

decijax is distributed under the terms of the MIT license.