{"id":15700368,"url":"https://github.com/soumik12345/generative-adversarial-networks","last_synced_at":"2026-01-20T13:01:21.767Z","repository":{"id":39737778,"uuid":"184021498","full_name":"soumik12345/Generative-Adversarial-Networks","owner":"soumik12345","description":"Implementations of various architectures and implementations of Generative Adversarial Networks","archived":false,"fork":false,"pushed_at":"2022-11-21T21:30:08.000Z","size":51362,"stargazers_count":2,"open_issues_count":4,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-07T06:18:46.677Z","etag":null,"topics":["conditional-gan","convolutional-neural-networks","gan","generative-adversarial-network","keras","multilayer-perceptron","neural-network","python","tensorflow","wasserstein-gan"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/soumik12345.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}},"created_at":"2019-04-29T07:27:25.000Z","updated_at":"2020-02-19T21:26:23.000Z","dependencies_parsed_at":"2022-08-29T00:21:22.297Z","dependency_job_id":null,"html_url":"https://github.com/soumik12345/Generative-Adversarial-Networks","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/soumik12345/Generative-Adversarial-Networks","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2FGenerative-Adversarial-Networks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2FGenerative-Adversarial-Networks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2FGenerative-Adversarial-Networks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2FGenerative-Adversarial-Networks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/soumik12345","download_url":"https://codeload.github.com/soumik12345/Generative-Adversarial-Networks/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/soumik12345%2FGenerative-Adversarial-Networks/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28603402,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-20T12:01:53.233Z","status":"ssl_error","status_checked_at":"2026-01-20T12:01:46.545Z","response_time":117,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["conditional-gan","convolutional-neural-networks","gan","generative-adversarial-network","keras","multilayer-perceptron","neural-network","python","tensorflow","wasserstein-gan"],"created_at":"2024-10-03T19:48:15.113Z","updated_at":"2026-01-20T13:01:21.745Z","avatar_url":"https://github.com/soumik12345.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Generative Adversarial Networks\n\n### 1. [MLP-GAN](./1-MLP-GAN/)\nSimple Generative Adversarial Network implemented using Multi Layered Perceptrons and trained on the MNIST dataset. The model can be generated by running the notebooks in the [notebooks](./1-MLP-GAN/notebooks/) folder. To test the pre-trained model run the `test_model.py` script.\n\nKaggle Kernel Link: [https://www.kaggle.com/soumikrakshit/generative-adversarial-network-in-tensorflow](https://www.kaggle.com/soumikrakshit/generative-adversarial-network-in-tensorflow)\n\n![MLP-GAN](./1-MLP-GAN/mlp-gan.png)\n\n### 2. [DCGAN](./2-DCGAN/)\nGenerative Adversarial Network implemented using Deep Convolutional Networks and trained on the MNIST dataset. The model can be generated by running the notebooks in the [notebooks](./2-DCGAN/notebooks/) folder. To test the pre-trained model run the `test_model.py` script.\n\nKaggle Kernel Link: [https://www.kaggle.com/soumikrakshit/dcgan-in-tensorflow](https://www.kaggle.com/soumikrakshit/dcgan-in-tensorflow)\n\n![DCGAN](./2-DCGAN/dcgan.png)\n\n### 3. [ACGAN](./3-ACGAN/)\nAuxiliary Classifier Generative Adversarial Network implemented using Deep Convolutional Networks and trained on the MNIST dataset. The model can be generated by running the notebooks in the [notebooks](./3-ACGAN/notebooks/) folder. To test the pre-trained model run the `test_model.py` script.\n\nKaggle Kernel Link: [https://www.kaggle.com/soumikrakshit/auxiliary-classifier-gan](https://www.kaggle.com/soumikrakshit/auxiliary-classifier-gan)\n\n![DCGAN](./3-ACGAN/acgan.png)\n\n### 4. [WGAN](./4-WGAN/)\nGenerative Adversarial Network implemented using Deep Convolutional Networks and Wassertein's Loss Function trained on the MNIST dataset. The model can be generated by running the notebooks in the [notebooks](./4-WGAN/notebooks/) folder. To test the pre-trained model run the `test_model.py` script.\n\nKaggle Kernel Link: [https://www.kaggle.com/soumikrakshit/wassertein-gan](https://www.kaggle.com/soumikrakshit/wassertein-gan)\n\n![WGAN](./4-WGAN/wgan.png)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsoumik12345%2Fgenerative-adversarial-networks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsoumik12345%2Fgenerative-adversarial-networks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsoumik12345%2Fgenerative-adversarial-networks/lists"}