| | |
| | |
Stat |
Members: 3645 Articles: 2'504'928 Articles rated: 2609
25 April 2024 |
|
| | | |
|
Article overview
| |
|
GPflowOpt: A Bayesian Optimization Library using TensorFlow | Nicolas Knudde
; Joachim van der Herten
; Tom Dhaene
; Ivo Couckuyt
; | Date: |
10 Nov 2017 | Abstract: | A novel Python framework for Bayesian optimization known as GPflowOpt is
introduced. The package is based on the popular GPflow library for Gaussian
processes, leveraging the benefits of TensorFlow including automatic
differentiation, parallelization and GPU computations for Bayesian
optimization. Design goals focus on a framework that is easy to extend with
custom acquisition functions and models. The framework is thoroughly tested and
well documented, and provides scalability. The current released version of
GPflowOpt includes some standard single-objective acquisition functions, the
state-of-the-art max-value entropy search, as well as a Bayesian
multi-objective approach. Finally, it permits easy use of custom modeling
strategies implemented in GPflow. | Source: | arXiv, 1711.3845 | Services: | Forum | Review | PDF | Favorites |
|
|
No review found.
Did you like this article?
Note: answers to reviews or questions about the article must be posted in the forum section.
Authors are not allowed to review their own article. They can use the forum section.
browser Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
|
| |
|
|
|
| News, job offers and information for researchers and scientists:
| |