{"id":16993694,"url":"https://github.com/cypriengille/semi-supervised-autoencoder","last_synced_at":"2025-03-22T05:24:07.481Z","repository":{"id":58779765,"uuid":"526608962","full_name":"CyprienGille/Semi-Supervised-AutoEncoder","owner":"CyprienGille","description":"A sparsified AutoEncoder to solve Semi-Supervised classification tasks","archived":false,"fork":false,"pushed_at":"2024-03-12T09:46:45.000Z","size":35758,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-01-27T06:13:32.288Z","etag":null,"topics":["autoencoder","biomedical","semisupervised-learning"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/CyprienGille.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2022-08-19T13:00:21.000Z","updated_at":"2024-07-03T16:15:11.000Z","dependencies_parsed_at":"2024-11-28T14:45:06.074Z","dependency_job_id":null,"html_url":"https://github.com/CyprienGille/Semi-Supervised-AutoEncoder","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CyprienGille%2FSemi-Supervised-AutoEncoder","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CyprienGille%2FSemi-Supervised-AutoEncoder/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CyprienGille%2FSemi-Supervised-AutoEncoder/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/CyprienGille%2FSemi-Supervised-AutoEncoder/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/CyprienGille","download_url":"https://codeload.github.com/CyprienGille/Semi-Supervised-AutoEncoder/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244910012,"owners_count":20530309,"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":["autoencoder","biomedical","semisupervised-learning"],"created_at":"2024-10-14T03:43:47.423Z","updated_at":"2025-03-22T05:24:07.463Z","avatar_url":"https://github.com/CyprienGille.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Semisupervised Autoencoder\n\nThis repository contains the code from :\n\n\u003e A new Semi-supervised classification method using a supervised autoencoder for biomedical applications, Gille C. and Guyard F. and Barlaud M., (2022). https://arxiv.org/abs/2208.10315 .\n\n## Repository contents\n\n - `script_semisupervised.py` : This is the main script used to produce the results shown in the paper. It generates plots in the `plots` directory, and saves results (metrics, losses...) as CSVs in the `results_semi` folder. All parameters are tunable near the start of the script.\n - `param_plots` : This is a helper script to reproduce the plots from Figures 2 and 3 of the aforementioned paper.\n - `script_eta_optimization.py` : This script is used to find the optimal sparsification parameter $\\eta$ either by dichotomy or using the [golden section strategy](https://en.wikipedia.org/wiki/Golden-section_search).\n - `functions` : Contains function utilities useful for the other main scripts.\n - `data` : Contains the two datasets presented in the paper.\n - `plots` and `results_semi` are results directories filled by executing `semisupervised_tests.py`.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcypriengille%2Fsemi-supervised-autoencoder","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcypriengille%2Fsemi-supervised-autoencoder","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcypriengille%2Fsemi-supervised-autoencoder/lists"}