{"id":19863957,"url":"https://github.com/sandialabs/shadow","last_synced_at":"2025-07-31T11:34:35.196Z","repository":{"id":57466146,"uuid":"238336704","full_name":"sandialabs/shadow","owner":"sandialabs","description":"Shadow semi-supervised consistency regularization PyTorch library","archived":false,"fork":false,"pushed_at":"2021-10-07T19:37:41.000Z","size":482,"stargazers_count":11,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-04-26T20:49:42.592Z","etag":null,"topics":["deep-learning","machine-learning","pytorch","scr-2444","semi-supervised-learning","snl-data-analysis"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sandialabs.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-02-05T00:35:37.000Z","updated_at":"2024-02-15T20:58:45.000Z","dependencies_parsed_at":"2022-08-31T02:11:19.938Z","dependency_job_id":null,"html_url":"https://github.com/sandialabs/shadow","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fshadow","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fshadow/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fshadow/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sandialabs%2Fshadow/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sandialabs","download_url":"https://codeload.github.com/sandialabs/shadow/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251992568,"owners_count":21677018,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["deep-learning","machine-learning","pytorch","scr-2444","semi-supervised-learning","snl-data-analysis"],"created_at":"2024-11-12T15:16:52.799Z","updated_at":"2025-05-02T05:30:32.236Z","avatar_url":"https://github.com/sandialabs.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"![Shadow](doc/source/figures/logo.png)\n======================================\n\n[![Build Status](https://app.travis-ci.com/sandialabs/shadow.svg?branch=master)](https://app.travis-ci.com/sandialabs/shadow)\n[![Coverage Status](https://coveralls.io/repos/github/sandialabs/shadow/badge.svg?branch=master)](https://coveralls.io/github/sandialabs/shadow?branch=master)\n[![Documentation Status](https://readthedocs.org/projects/shadow-ssml/badge/?version=latest)](https://shadow-ssml.readthedocs.io/en/latest/?badge=latest)\n[![Downloads](https://pepy.tech/badge/shadow-ssml)](https://pepy.tech/project/shadow-ssml)\n\nShadow is a [PyTorch](https://pytorch.org/) based library for semi-supervised machine learning.\nThe `shadow` python 3 package includes implementations of Virtual Adversarial Training,\nMean Teacher, and Exponential Averaging Adversarial Training.\nSemi-supervised learning enables training a model (gold dashed line) from both labeled (red and\nblue) and unlabeled (grey) data, and is typically used in contexts in which labels are expensive\nto obtain but unlabeled examples are plentiful.\n\n![SSML for half moons](doc/source/figures/ssml-halfmoons.png)\n\nFor more information, go to https://shadow-ssml.readthedocs.io/en/latest/\n\nInstallation\n------------\nShadow can by installed directly from pypi as:\n```\npip install shadow-ssml\n```\n\nCiting Shadow\n--------------\n* Linville, L., Anderson, D., Michalenko, J., Galasso, J., \u0026 Draelos, T. (2021). Semisupervised Learning for Seismic Monitoring Applications. Seismological Society of America, 92(1), 388-395. doi: https://doi.org/10.1785/0220200195\n\nLicense\n-------\nRevised BSD. See the LICENSE.txt file.\n\nContact\n-------\n* Dylan Anderson, Sandia National Laboratories, dzander@sandia.gov\n* Lisa Linville, Sandia National Laboratories, llinvil@sandia.gov\n\nSandia 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.\n\nCopyright\n---------\nCopyright 2019, National Technology \u0026 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.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Fshadow","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsandialabs%2Fshadow","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsandialabs%2Fshadow/lists"}