{"id":27170465,"url":"https://github.com/edserranoc/inverse_problems_course","last_synced_at":"2025-04-09T07:56:25.620Z","repository":{"id":283755464,"uuid":"952811958","full_name":"edserranoc/Inverse_Problems_Course","owner":"edserranoc","description":"Inverse Problems Course.","archived":false,"fork":false,"pushed_at":"2025-03-22T01:14:42.000Z","size":2859,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-22T01:21:51.513Z","etag":null,"topics":["bayesian-inference","mcmc-sampling","regularization-methods","variational-inference"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/edserranoc.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":"2025-03-21T23:39:16.000Z","updated_at":"2025-03-22T01:14:45.000Z","dependencies_parsed_at":"2025-03-22T01:33:20.718Z","dependency_job_id":null,"html_url":"https://github.com/edserranoc/Inverse_Problems_Course","commit_stats":null,"previous_names":["edserranoc/inverse-problems"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/edserranoc%2FInverse_Problems_Course","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/edserranoc%2FInverse_Problems_Course/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/edserranoc%2FInverse_Problems_Course/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/edserranoc%2FInverse_Problems_Course/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/edserranoc","download_url":"https://codeload.github.com/edserranoc/Inverse_Problems_Course/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247999851,"owners_count":21031045,"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":["bayesian-inference","mcmc-sampling","regularization-methods","variational-inference"],"created_at":"2025-04-09T07:56:25.017Z","updated_at":"2025-04-09T07:56:25.609Z","avatar_url":"https://github.com/edserranoc.png","language":"Jupyter Notebook","readme":"# Inverse-Problems\n\nThis repository contains the assignments and final project for the \"Inverse Problems\" taught by Dr. [Marcos Aurelio Capistrán Ocampo](https://salud.conahcyt.mx/coronavirus/investigacion/investigadores/maco.html) at CIMAT (Centro de Investigación en Matemáticas), developed in the Python programming language. The code is written in Spanish.\n\n## Final Project\n### Review of Stein Variational Gradient Descend Method\nReviewed PyTorch implementations of Stein variational methods, analyzed algorithms, and conducted sampling simulations. The code is based on the notebook provided in [[4](https://github.com/activatedgeek/svgd)], with some modifications.\n\n**Mixture of Six Gaussians**\n\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"./images/mixture_6_gaussians.png\" width=\"600\"/\u003e \n\u003c/div\u003e\n\n**Banana-shaped distribution:**\n\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"./images/Unnormalized_Distribution.png\" width=\"600\"/\u003e \n\u003c/div\u003e\n\n\n## Assigments\n### Metropolis-Hastings Algorithm \n\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"./images/Metropolis.png\" width=\"600\"/\u003e \n\u003c/div\u003e\n\n### Landweber and Kaczmarz Method\n\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"./images/iteration_methods.png\" width=\"700\"/\u003e \n\u003c/div\u003e\n\n\n### TSVD and Tikhonov Regularizations\n\u003cdiv align=\"center\"\u003e\n\u003cimg src=\"./images/tikhonov_tsvd.png\" width=\"600\"/\u003e \n\u003c/div\u003e\n\n\n\n\n\n## Reference\n1. Kaipio, J., \u0026 Somersalo, E. (2006). Statistical and computational inverse problems (Vol. 160). Springer Science \u0026 Business Media.\n2. Vogel, C. R. (2002). Computational methods for inverse problems. Society for Industrial and Applied Mathematics.\n3. Liu, Q., \u0026 Wang, D. (2016). Stein variational gradient descent: A general purpose bayesian inference algorithm. Advances in neural information processing systems, 29.\n4. PyTorch implementation of Stein Variational Gradient Descent. https://github.com/activatedgeek/svgd\n5. Anzengruber, S. W., \u0026 Ramlau, R. (2009). Morozov's discrepancy principle for Tikhonov-type functionals with nonlinear operators. Inverse Problems, 26(2), 025001.\n## License\nThis project is licensed under the GPL-3.0 license. See the LICENSE file for details.","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fedserranoc%2Finverse_problems_course","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fedserranoc%2Finverse_problems_course","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fedserranoc%2Finverse_problems_course/lists"}