About BayesO¶
Simple, but essential Bayesian optimization package. It is designed to run advanced Bayesian optimization with implementation-specific and application-specific modifications as well as to run Bayesian optimization in various applications simply. This package contains the codes for Gaussian process regression and Gaussian process-based Bayesian optimization. Some famous benchmark and custom benchmark functions for Bayesian optimization are included in bayeso-benchmarks, which can be used to test the Bayesian optimization strategy. If you are interested in this package, please refer to that repository.
Supported Python Version¶
We test our package in the following versions.
- Python 3.6
- Python 3.7
- Python 3.8
- Python 3.9
Contributor¶
- Jungtaek Kim (POSTECH)
Citation¶
@misc{KimJ2017bayeso,
author={Kim, Jungtaek and Choi, Seungjin},
title={{BayesO}: A {Bayesian} optimization framework in {Python}},
howpublished={\url{http://bayeso.org}},
year={2017}
}
Contact¶
- Jungtaek Kim: jtkim@postech.ac.kr