{"id":13689189,"url":"https://github.com/probabilistic-numerics/probnum","last_synced_at":"2025-05-01T23:32:56.615Z","repository":{"id":37981919,"uuid":"218856084","full_name":"probabilistic-numerics/probnum","owner":"probabilistic-numerics","description":"Probabilistic Numerics in Python.","archived":false,"fork":false,"pushed_at":"2024-05-01T06:10:27.000Z","size":161483,"stargazers_count":429,"open_issues_count":72,"forks_count":56,"subscribers_count":8,"default_branch":"main","last_synced_at":"2024-08-03T15:16:12.784Z","etag":null,"topics":["machine-learning","numerical-methods","probabilistic-numerics"],"latest_commit_sha":null,"homepage":"http://probnum.org","language":"Python","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/probabilistic-numerics.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":".github/CODEOWNERS","security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-10-31T20:29:11.000Z","updated_at":"2024-08-01T09:33:13.000Z","dependencies_parsed_at":"2023-02-16T10:31:26.503Z","dependency_job_id":"19679792-d734-4af3-ac4b-da4e07a0132c","html_url":"https://github.com/probabilistic-numerics/probnum","commit_stats":null,"previous_names":[],"tags_count":29,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/probabilistic-numerics%2Fprobnum","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/probabilistic-numerics%2Fprobnum/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/probabilistic-numerics%2Fprobnum/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/probabilistic-numerics%2Fprobnum/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/probabilistic-numerics","download_url":"https://codeload.github.com/probabilistic-numerics/probnum/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":224282178,"owners_count":17285783,"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":["machine-learning","numerical-methods","probabilistic-numerics"],"created_at":"2024-08-02T15:01:37.491Z","updated_at":"2024-11-12T13:31:04.130Z","avatar_url":"https://github.com/probabilistic-numerics.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n    \u003ca href=\"https://probnum.readthedocs.io\"\u003e\u003cimg align=\"center\" src=\"https://raw.githubusercontent.com/probabilistic-numerics/probnum/main/docs/source/assets/img/logo/probnum_logo_dark_txtbelow.svg\" alt=\"probabilistic numerics\" width=\"400\" style=\"padding-right: 10px; padding left: 10px;\" title=\"Probabilistic Numerics in Python\"/\u003e\n    \u003c/a\u003e\n    \u003ch3\u003eLearn to Approximate. Approximate to Learn.\u003c/h3\u003e\n    \u003cp\u003eProbabilistic Numerics in Python.\u003c/p\u003e\n\u003c/div\u003e\n\n---\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ch4 align=\"center\"\u003e\n  \u003ca href=\"https://probnum.readthedocs.io\"\u003eHome\u003c/a\u003e |\n  \u003ca href=\"https://probnum.readthedocs.io/en/latest/tutorials.html\"\u003eTutorials\u003c/a\u003e |  \n  \u003ca href=\"https://probnum.readthedocs.io/en/latest/api.html\"\u003eAPI Reference\u003c/a\u003e |\n  \u003ca href=\"https://probnum.readthedocs.io/en/latest/development.html\"\u003eContributing\u003c/a\u003e\n\u003c/h4\u003e\n\n[![CI build](https://img.shields.io/github/actions/workflow/status/probabilistic-numerics/probnum/CI-build.yml?branch=main\u0026style=flat-square\u0026logo=github\u0026logoColor=white\u0026label=CI-build)](https://github.com/probabilistic-numerics/probnum/actions?query=workflow%3ACI-build)\n[![Coverage Status](https://img.shields.io/codecov/c/gh/probabilistic-numerics/probnum/main?style=flat-square\u0026label=Coverage\u0026logo=codecov\u0026logoColor=white)](https://codecov.io/gh/probabilistic-numerics/probnum/branch/main)\n[![Benchmarks](http://img.shields.io/badge/Benchmarks-asv-blueviolet.svg?style=flat-square\u0026logo=swift\u0026logoColor=white)](https://probabilistic-numerics.github.io/probnum-benchmarks/benchmarks/)\n[![PyPI](https://img.shields.io/pypi/v/probnum?style=flat-square\u0026label=PyPI\u0026logo=pypi\u0026logoColor=white)](https://pypi.org/project/probnum/)\n\n\u003c/div\u003e\n\n---\n\n**ProbNum** is a Python toolkit for solving numerical problems in linear algebra, optimization, quadrature and\ndifferential equations. ProbNum solvers not only estimate the solution of the numerical problem, but also its uncertainty (numerical error) which arises from finite computational resources, discretization and stochastic input. This numerical uncertainty can be used in downstream decisions.\n\nCurrently, available solvers are:\n\n- **Linear solvers:** Solve $A x = b$ for $x$.\n- **ODE solvers:** Solve $\\dot{y}(t) = f(y(t), t)$ for $y$.\n- **Integral solvers (quadrature):** Solve $F = \\int_D f(x) \\mathrm{d}p(x)$ for $F$.\n\nLower level structure includes:\n\n- **Random variables and random processes**, as well as arithmetic operations thereof.\n- Memory-efficient and lazy implementation of **linear operators**.\n- **Filtering and smoothing** for (probabilistic) state-space models, mostly variants of Kalman filters.\n\nProbNum is underpinned by the research field probabilistic numerics (PN), which lies at the intersection of machine learning and numerics.\nPN aims to quantify uncertainty arising from intractable or incomplete numerical computation and from stochastic input \nusing the tools of probability theory. The general vision of probabilistic numerics is to provide well-calibrated \nprobability measures over the output of a numerical routine, which then can be propagated along the chain of \ncomputation.\n\n\n## Installation\nTo get started install ProbNum using `pip`.\n```bash\npip install probnum\n```\nAlternatively, you can install the latest version from source.\n```bash\npip install git+https://github.com/probabilistic-numerics/probnum.git\n```\n\n\u003e Note: This package is currently work in progress, therefore interfaces are subject to change.\n\n## Documentation and Examples\nFor tips on getting started and how to use this package please refer to the\n[**documentation**](https://probnum.readthedocs.io). It contains a \n[quickstart guide](https://probnum.readthedocs.io/en/latest/tutorials/quickstart.html) \nand Jupyter notebooks illustrating the basic usage of the ProbNum solvers.\n\n## Package Development\nThis repository is currently under development and benefits from contribution to the code, examples or documentation.\nPlease refer to the [contribution guidelines](https://probnum.readthedocs.io/en/latest/development.html) before\nmaking a pull request.\n\nA list of core contributors to ProbNum can be found\n[here](https://probnum.readthedocs.io/en/latest/development.html#probnum-team).\n\n## Citing ProbNum\nIf you are using ProbNum in your research, please cite as provided. \nThe \"Cite this repository\" button on the sidebar generates a BibTeX entry or an APA entry. \n\n## License and Contact\nThis work is released under the [MIT License](https://github.com/probabilistic-numerics/probnum/blob/main/LICENSE.txt).\n\nPlease submit an [issue on GitHub](https://github.com/probabilistic-numerics/probnum/issues/new) to report bugs or\nrequest changes.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprobabilistic-numerics%2Fprobnum","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fprobabilistic-numerics%2Fprobnum","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fprobabilistic-numerics%2Fprobnum/lists"}