Skip to main content

Semi-supervised machine learning for PyTorch.

Project description

Shadow

Build Status Coverage Status Documentation Status Downloads

Shadow is a PyTorch based library for semi-supervised machine learning. The shadow python 3 package includes implementations of Virtual Adversarial Training, Mean Teacher, and Exponential Averaging Adversarial Training. Semi-supervised learning enables training a model (gold dashed line) from both labeled (red and blue) and unlabeled (grey) data, and is typically used in contexts in which labels are expensive to obtain but unlabeled examples are plentiful.

SSML for half moons

For more information, go to https://shadow-ssml.readthedocs.io/en/latest/

Installation

Shadow can by installed directly from pypi as:

pip install shadow-ssml

Citing Shadow

  • Linville, Lisa, et al. "Semi-supervised learning for seismic monitoring applications". In preparation. (2020).

License

Revised BSD. See the LICENSE.txt file.

Contact

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Project details


Download files

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

Files for shadow-ssml, version 1.0.0
Filename, size File type Python version Upload date Hashes
Filename, size shadow-ssml-1.0.0.tar.gz (12.2 kB) File type Source Python version None Upload date Hashes View

Supported by

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