{"id":15683917,"url":"https://github.com/sayakpaul/adamatch-tf","last_synced_at":"2026-03-05T17:07:45.918Z","repository":{"id":106647138,"uuid":"378403189","full_name":"sayakpaul/AdaMatch-TF","owner":"sayakpaul","description":"Includes additional materials for the following keras.io blog post.","archived":false,"fork":false,"pushed_at":"2021-06-23T02:09:06.000Z","size":1124,"stargazers_count":12,"open_issues_count":0,"forks_count":5,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-31T11:01:44.438Z","etag":null,"topics":["keras","semi-supervised-learning","tensorflow","unsupervised-domain-adaptation","vision","weak-supervision"],"latest_commit_sha":null,"homepage":"https://keras.io/examples/vision/adamatch/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sayakpaul.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-06-19T12:08:37.000Z","updated_at":"2023-10-22T14:39:13.000Z","dependencies_parsed_at":null,"dependency_job_id":"6d730702-6b96-44d4-9ea9-720fdfe39179","html_url":"https://github.com/sayakpaul/AdaMatch-TF","commit_stats":{"total_commits":12,"total_committers":1,"mean_commits":12.0,"dds":0.0,"last_synced_commit":"c1fac6b42fa5dc0a5a299ccd736e28ed7657e094"},"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2FAdaMatch-TF","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2FAdaMatch-TF/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2FAdaMatch-TF/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sayakpaul%2FAdaMatch-TF/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sayakpaul","download_url":"https://codeload.github.com/sayakpaul/AdaMatch-TF/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252895790,"owners_count":21821218,"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":["keras","semi-supervised-learning","tensorflow","unsupervised-domain-adaptation","vision","weak-supervision"],"created_at":"2024-10-03T17:09:13.987Z","updated_at":"2026-03-05T17:07:45.881Z","avatar_url":"https://github.com/sayakpaul.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AdaMatch-TF\nIncludes additional materials for the following keras.io blog post: [Semi-supervision and domain adaptation with AdaMatch](https://keras.io/examples/vision/adamatch/).\n\n## About the notebooks\n\n* `AdaMatch.ipynb`: Original notebook submitted for the [PR](https://github.com/keras-team/keras-io/pull/513).\n* `Vanilla_WideResNet.ipynb`: Trains a WideResNet-28-2 on MNIST (source domain) and evaluates on the SVHN dataset (target domain). The model trained in this notebook serves as the baseline. \n\n## Acknowledgements\n\n* François Chollet for helping with the implementation.\n* [ML-GDE](https://developers.google.com/programs/experts/) program for providing GCP credits that supported the experiments. \n\n## Paper citation\n\n```\n@misc{berthelot2021adamatch,\n      title={AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation}, \n      author={David Berthelot and Rebecca Roelofs and Kihyuk Sohn and Nicholas Carlini and Alex Kurakin},\n      year={2021},\n      eprint={2106.04732},\n      archivePrefix={arXiv},\n      primaryClass={cs.LG}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsayakpaul%2Fadamatch-tf","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsayakpaul%2Fadamatch-tf","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsayakpaul%2Fadamatch-tf/lists"}