{"id":13408323,"url":"https://github.com/wiseodd/generative-models","last_synced_at":"2025-05-14T04:07:32.393Z","repository":{"id":38107524,"uuid":"75829600","full_name":"wiseodd/generative-models","owner":"wiseodd","description":"Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.","archived":false,"fork":false,"pushed_at":"2024-03-24T20:38:46.000Z","size":114,"stargazers_count":7408,"open_issues_count":22,"forks_count":2034,"subscribers_count":298,"default_branch":"master","last_synced_at":"2025-05-10T05:42:01.955Z","etag":null,"topics":["gan","generative-model","machine-learning","pytorch","rbm","restricted-boltzmann-machine","tensorflow","vae"],"latest_commit_sha":null,"homepage":"http://wiseodd.github.io","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"unlicense","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/wiseodd.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":"2016-12-07T11:28:16.000Z","updated_at":"2025-05-09T20:41:26.000Z","dependencies_parsed_at":"2024-09-24T13:38:52.449Z","dependency_job_id":null,"html_url":"https://github.com/wiseodd/generative-models","commit_stats":{"total_commits":105,"total_committers":7,"mean_commits":15.0,"dds":"0.22857142857142854","last_synced_commit":"b930d5fa9e2f69adfd4ea8ec759f38f6ce6da4c2"},"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wiseodd%2Fgenerative-models","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wiseodd%2Fgenerative-models/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wiseodd%2Fgenerative-models/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/wiseodd%2Fgenerative-models/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/wiseodd","download_url":"https://codeload.github.com/wiseodd/generative-models/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254069211,"owners_count":22009507,"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":["gan","generative-model","machine-learning","pytorch","rbm","restricted-boltzmann-machine","tensorflow","vae"],"created_at":"2024-07-30T20:00:52.159Z","updated_at":"2025-05-14T04:07:32.359Z","avatar_url":"https://github.com/wiseodd.png","language":"Python","readme":"# Generative Models\nCollection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.\nAlso present here are RBM and Helmholtz Machine.\n\n## Note:\nGenerated samples will be stored in `GAN/{gan_model}/out` (or `VAE/{vae_model}/out`, etc) directory during training.\n\n## What's in it?\n\n#### Generative Adversarial Nets (GAN)\n  1. [Vanilla GAN](https://arxiv.org/abs/1406.2661)\n  2. [Conditional GAN](https://arxiv.org/abs/1411.1784)\n  3. [InfoGAN](https://arxiv.org/abs/1606.03657)\n  4. [Wasserstein GAN](https://arxiv.org/abs/1701.07875)\n  5. [Mode Regularized GAN](https://arxiv.org/abs/1612.02136)\n  6. [Coupled GAN](https://arxiv.org/abs/1606.07536)\n  7. [Auxiliary Classifier GAN](https://arxiv.org/abs/1610.09585)\n  8. [Least Squares GAN](https://arxiv.org/abs/1611.04076v2)\n  9. [Boundary Seeking GAN](https://arxiv.org/abs/1702.08431)\n  10. [Energy Based GAN](https://arxiv.org/abs/1609.03126)\n  11. [f-GAN](https://arxiv.org/abs/1606.00709)\n  12. [Generative Adversarial Parallelization](https://arxiv.org/abs/1612.04021)\n  13. [DiscoGAN](https://arxiv.org/abs/1703.05192)\n  14. [Adversarial Feature Learning](https://arxiv.org/abs/1605.09782) \u0026 [Adversarially Learned Inference](https://arxiv.org/abs/1606.00704)\n  15. [Boundary Equilibrium GAN](https://arxiv.org/abs/1703.10717)\n  16. [Improved Training for Wasserstein GAN](https://arxiv.org/abs/1704.00028)\n  17. [DualGAN](https://arxiv.org/abs/1704.02510)\n  18. [MAGAN: Margin Adaptation for GAN](https://arxiv.org/abs/1704.03817)\n  19. [Softmax GAN](https://arxiv.org/abs/1704.06191)\n  20. [GibbsNet](https://papers.nips.cc/paper/7094-gibbsnet-iterative-adversarial-inference-for-deep-graphical-models.pdf)\n\n#### Variational Autoencoder (VAE)\n  1. [Vanilla VAE](https://arxiv.org/abs/1312.6114)\n  2. [Conditional VAE](https://arxiv.org/abs/1406.5298)\n  3. [Denoising VAE](https://arxiv.org/abs/1511.06406)\n  4. [Adversarial Autoencoder](https://arxiv.org/abs/1511.05644)\n  5. [Adversarial Variational Bayes](https://arxiv.org/abs/1701.04722)\n\n#### Restricted Boltzmann Machine (RBM)\n  1. [Binary RBM with Contrastive Divergence](http://www.cs.toronto.edu/~fritz/absps/cdmiguel.pdf)\n  2. [Binary RBM with Persistent Contrastive Divergence](http://www.cs.toronto.edu/~tijmen/pcd/pcd.pdf)\n\n#### Helmholtz Machine\n  1. [Binary Helmholtz Machine with Wake-Sleep Algorithm](http://www.cs.toronto.edu/~fritz/absps/ws.pdf)\n\n## Dependencies\n\n1. Install miniconda \u003chttp://conda.pydata.org/miniconda.html\u003e\n2. Do `conda env create`\n3. Enter the env `source activate generative-models`\n4. Install [Tensorflow](https://www.tensorflow.org/get_started/os_setup)\n5. Install [Pytorch](https://github.com/pytorch/pytorch#installation)\n","funding_links":[],"categories":["Recommendations","Uncategorized","Python","Machine Learning","Pytorch elsewhere ｜ Pytorch相关","Pytorch elsewhere","Implementations of various types of GANs collection","Artificial Intelligence \u0026 Data Science"],"sub_categories":["Uncategorized","JavaScript","Other libraries｜其他库:","Other libraries:","3D Object generation","Machine Learning \u0026 Neural Networks"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwiseodd%2Fgenerative-models","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fwiseodd%2Fgenerative-models","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fwiseodd%2Fgenerative-models/lists"}