{"id":26387879,"url":"https://github.com/qiauil/distrans","last_synced_at":"2025-07-07T05:01:52.506Z","repository":{"id":255364451,"uuid":"849363802","full_name":"qiauil/distrans","owner":"qiauil","description":"A PyTorch Library for Distribution Transformation in Generative Modeling​","archived":false,"fork":false,"pushed_at":"2024-11-07T15:58:43.000Z","size":1975,"stargazers_count":3,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-06-10T00:05:32.194Z","etag":null,"topics":["diffusion-models","flowmatching","generative-model"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/qiauil.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,"zenodo":null}},"created_at":"2024-08-29T13:14:13.000Z","updated_at":"2024-11-14T10:38:13.000Z","dependencies_parsed_at":"2024-08-29T15:04:11.960Z","dependency_job_id":"3c15ae93-fa6b-485d-9116-a955bebae209","html_url":"https://github.com/qiauil/distrans","commit_stats":null,"previous_names":["qiauil/distrans"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/qiauil/distrans","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qiauil%2Fdistrans","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qiauil%2Fdistrans/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qiauil%2Fdistrans/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qiauil%2Fdistrans/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/qiauil","download_url":"https://codeload.github.com/qiauil/distrans/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/qiauil%2Fdistrans/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264016713,"owners_count":23544623,"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":["diffusion-models","flowmatching","generative-model"],"created_at":"2025-03-17T08:37:57.681Z","updated_at":"2025-07-07T05:01:52.455Z","avatar_url":"https://github.com/qiauil.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003e\r\n  \u003cimg src=\"./assets/flow.png\" width=\"128\"/\u003e\r\n\u003c/h1\u003e\r\n\u003ch4 align=\"center\"\u003edistrans\u003c/h4\u003e\r\n\u003ch6 align=\"center\"\u003eA PyTorch Library for Distribution Transformation in Generative Modeling\u003c/h6\u003e\r\n\r\n## Installation\r\n\r\n* Install the latest version through pip: `pip install git+https://github.com/qiauil/distrans`\r\n* Install locally: Download the repository and run `./install.sh` or `pip install .`\r\n\r\n## Playground\r\n\r\n* Distribution transformation from Gaussian: [gaussian.ipynb](https://github.com/qiauil/distrans/blob/main/gaussian.ipynb)\r\n* Transform moons distribution to swiss distribution: [moons2swiss.ipynb](https://github.com/qiauil/distrans/blob/main/moons2swiss.ipynb)\r\n\r\n\r\n## Additional Info\r\n\r\nThis work is part of our physics-based deep learning research, please visit [the website of our research group at TUM](https://ge.in.tum.de/publications/) for more information.\r\n\r\n## Useful reference\r\n\r\n### Diffusion\r\n* [***Denoising Diffusion Probabilistic Models***, Jonathan Ho, Ajay Jain and Pieter Abbeel, NeurIPS, 2020](https://arxiv.org/abs/2006.11239)\r\n* [***Diffusion Models Beat GANs on Image Synthesis***, Prafulla Dhariwal and Alex Nichol, NeurIPS, 2021](https://arxiv.org/abs/2105.05233)\r\n### Flow Matching\r\n* [***Flow Matching for Generative Modeling***, Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, and Matthew Le, ICLR, 2023](https://arxiv.org/abs/2210.02747)\r\n* [***Improving and generalizing flow-based generative models with minibatch optimal transport***, Alexander Tong, Kilian Fatras, Nikolay Malkin, Guillaume Huguet, Yanlei Zhang, Jarrid Rector-Brooks, Guy Wolf and Yoshua Bengio, TMLR, 2024](https://arxiv.org/abs/2302.00482)\r\n* [***An introduction to Flow Matching***, Fjelde, Tor and Mathieu, Emile and Dutordoir, Vincent, 2024](https://mlg.eng.cam.ac.uk/blog/2024/01/20/flow-matching.html)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqiauil%2Fdistrans","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fqiauil%2Fdistrans","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fqiauil%2Fdistrans/lists"}