Skip to main content

Bayesian Optimization Library with GPU support

Project description

Bayesian Optimization Library

The bayesian optimization algorithm is a surrogate-based optimizer that can
optimize expensive black-box functions. This implementation is specifically
tuned to optimize deel neural networks. It is able to handle paralell
evaluations on multiple GPUs, and can use a Random Forest surrogate model.

For additional details see our paper: <https://coming_soon>`_.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ParallelBayesOpt-0.9.2.tar.gz (13.2 kB view hashes)

Uploaded source

Built Distribution

ParallelBayesOpt-0.9.2-py2.py3-none-any.whl (12.2 kB view hashes)

Uploaded py2 py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page