https://github.com/sandialabs/shadow

Shadow semi-supervised consistency regularization PyTorch library
https://github.com/sandialabs/shadow

deep-learning machine-learning pytorch scr-2444 semi-supervised-learning snl-data-analysis

Last synced: 11 months ago
JSON representation

Shadow semi-supervised consistency regularization PyTorch library

• Host: GitHub
• URL: https://github.com/sandialabs/shadow
• Owner: sandialabs
• License: bsd-3-clause
• Created: 2020-02-05T00:35:37.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-10-07T19:37:41.000Z (almost 5 years ago)
• Last Synced: 2024-04-26T20:49:42.592Z (about 2 years ago)
• Topics: deep-learning, machine-learning, pytorch, scr-2444, semi-supervised-learning, snl-data-analysis
• Language: Python
• Homepage:
• Size: 471 KB
• Stars: 11
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

Awesome Lists containing this project

README

          
![Shadow](doc/source/figures/logo.png)

======================================

[![Build Status](https://app.travis-ci.com/sandialabs/shadow.svg?branch=master)](https://app.travis-ci.com/sandialabs/shadow)

[![Coverage Status](https://coveralls.io/repos/github/sandialabs/shadow/badge.svg?branch=master)](https://coveralls.io/github/sandialabs/shadow?branch=master)

[![Documentation Status](https://readthedocs.org/projects/shadow-ssml/badge/?version=latest)](https://shadow-ssml.readthedocs.io/en/latest/?badge=latest)

[![Downloads](https://pepy.tech/badge/shadow-ssml)](https://pepy.tech/project/shadow-ssml)

Shadow is a [PyTorch](https://pytorch.org/) 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](doc/source/figures/ssml-halfmoons.png)

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, L., Anderson, D., Michalenko, J., Galasso, J., & Draelos, T. (2021). Semisupervised Learning for Seismic Monitoring Applications. Seismological Society of America, 92(1), 388-395. doi: https://doi.org/10.1785/0220200195

License

-------

Revised BSD. See the LICENSE.txt file.

Contact

-------

* Dylan Anderson, Sandia National Laboratories, dzander@sandia.gov

* Lisa Linville, Sandia National Laboratories, llinvil@sandia.gov

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.

Copyright

---------

Copyright 2019, National Technology & Engineering Solutions of Sandia, LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights in this software.