{"id":21187776,"url":"https://github.com/vasukalariya/generative-modelling","last_synced_at":"2026-05-11T06:53:33.231Z","repository":{"id":213975518,"uuid":"253263425","full_name":"vasukalariya/Generative-Modelling","owner":"vasukalariya","description":"Implementation of various generative models using PyTorch.","archived":false,"fork":false,"pushed_at":"2020-09-05T06:51:04.000Z","size":2300,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-21T13:08:49.871Z","etag":null,"topics":["conditional-gan","dcgan","gan","generative-model","image-reconstruction","mnist","neural-network","numpy","pytorch","rbm","restricted-boltzmann-machine","vae","variational-autoencoder"],"latest_commit_sha":null,"homepage":"","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/vasukalariya.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}},"created_at":"2020-04-05T15:10:58.000Z","updated_at":"2024-04-12T04:59:27.000Z","dependencies_parsed_at":"2023-12-24T20:40:52.987Z","dependency_job_id":null,"html_url":"https://github.com/vasukalariya/Generative-Modelling","commit_stats":null,"previous_names":["vasukalariya/generative-modelling"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vasukalariya%2FGenerative-Modelling","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vasukalariya%2FGenerative-Modelling/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vasukalariya%2FGenerative-Modelling/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vasukalariya%2FGenerative-Modelling/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vasukalariya","download_url":"https://codeload.github.com/vasukalariya/Generative-Modelling/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243640512,"owners_count":20323674,"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":["conditional-gan","dcgan","gan","generative-model","image-reconstruction","mnist","neural-network","numpy","pytorch","rbm","restricted-boltzmann-machine","vae","variational-autoencoder"],"created_at":"2024-11-20T18:41:00.137Z","updated_at":"2026-05-11T06:53:33.186Z","avatar_url":"https://github.com/vasukalariya.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Restricted Boltzmann Machines\n![RBM Image](rbm.png)\n## Implementation Details\n* The implemented RBM consist of 2 layers with 784 visible units and 256 hidden units.\n* Trained using K-Contrastive Divergence with k = 1.\n* The RBM can be modified as per the use.\n* It is built solely from scratch using NumPy.\n* It is trained for MNIST Reconstruction and learning its probability distribution.\n* Trained on 60000 images.\n* It is modular in nature so you could change the parameters as per your choice.\n\n## How to Use\n* Download the train_images from [here](https://raw.githubusercontent.com/sebastianlapuschkin/lrp_toolbox/master/data/MNIST/train_images.npy)\n* For sample demonstration a clipped image is reconstructed using trained RBM.\n* The notebook is ready to run.\n\n# Generative Adversarial Networks\n![GAN Image](gan.jpg)\n# Variational Autoencoders\n![VAE Image](vae.png)\n## For learning\n* To learn the concepts please watch the [videos](https://www.youtube.com/watch?v=lXrFX3vjtjQ\u0026list=PL3pGy4HtqwD2kwldm81pszxZDJANK3uGV\u0026index=135)\n* The notations are also similar.\n\n\n\n### Have Fun! Learning :smiley:\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvasukalariya%2Fgenerative-modelling","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvasukalariya%2Fgenerative-modelling","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvasukalariya%2Fgenerative-modelling/lists"}