google-research / hyperbo
Pre-trained Gaussian processes for Bayesian optimization
Why this job: matched by what the repo talks about: gaussian, optimization, train
What it does
A Jax/Flax codebase for the algorithm in HyperBO described in *Pre-trained Gaussian processes for Bayesian optimization* published in the Journal of Machine Learning Research (JMLR).
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 36 days ago
- Stars
- 109
- On GitHub
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 93% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 0% closed
- 6 still open
- Pull requests
- 30 merged
- 5 waiting
- Releases
- None
- Never published
- Contributing guide (opens in new tab)
- No security policy
- No code of conduct
More: languages, topics and project record
Languages
- Python 93%
- Jupyter Notebook 7%
Topics
- bayesian-methods
- bayesian-optimization
- deep-learning
- hyperparameter-tuning
- machine-learning
Project record
- Job3D and Blender
- StatusListed
- Commits71
- Forks9
- Watching3
- Stars in 28 days+2
- CreatedOct 19, 2021
- First seen by usNov 7, 2026
- CheckedNov 8, 2026