Implementation of random fourier feature (RFF) approximations and Thompson sampling.
Project description
pyrff: Approximating Gaussian Process samples with Random Fourier Features
This project is a Python implementation of random fourier feature (RFF) approximations [1].
It is heavily inspired by the implementations from [2, 3] and generalizes the implementation to work with GP hyperparameters obtained from any GP library.
Examples are given as Jupyter notebooks for GPs fitted with PyMC3 and scikit-learn:
Installation
pyrff is released on PyPI:
pip install pyrff
Usage and Citing
pyrff is licensed under the GNU Affero General Public License v3.0.
Head over to Zenodo to generate a BibTeX citation for the latest release.
References
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