{"id":16863616,"url":"https://github.com/jonathanwenger/itergp","last_synced_at":"2026-02-27T03:32:34.613Z","repository":{"id":62744043,"uuid":"454216216","full_name":"JonathanWenger/itergp","owner":"JonathanWenger","description":"IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)","archived":false,"fork":false,"pushed_at":"2023-04-12T14:00:38.000Z","size":20884,"stargazers_count":40,"open_issues_count":1,"forks_count":2,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-04T04:41:20.417Z","etag":null,"topics":["gaussian-processes","machine-learning","neurips-2022","numerical-linear-algebra","probabilistic-numerics"],"latest_commit_sha":null,"homepage":"https://itergp.readthedocs.io","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/JonathanWenger.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":"2022-02-01T00:30:47.000Z","updated_at":"2024-12-14T18:03:15.000Z","dependencies_parsed_at":"2024-10-28T18:02:46.983Z","dependency_job_id":null,"html_url":"https://github.com/JonathanWenger/itergp","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/JonathanWenger/itergp","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JonathanWenger%2Fitergp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JonathanWenger%2Fitergp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JonathanWenger%2Fitergp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JonathanWenger%2Fitergp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/JonathanWenger","download_url":"https://codeload.github.com/JonathanWenger/itergp/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JonathanWenger%2Fitergp/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29883735,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-26T23:51:21.483Z","status":"online","status_checked_at":"2026-02-27T02:00:06.759Z","response_time":57,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":["gaussian-processes","machine-learning","neurips-2022","numerical-linear-algebra","probabilistic-numerics"],"created_at":"2024-10-13T14:39:09.545Z","updated_at":"2026-02-27T03:32:34.588Z","avatar_url":"https://github.com/JonathanWenger.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cbr\u003e\n\u003cdiv align=\"center\"\u003e\n    \u003cimg align=\"center\" src=\"docs/source/assets/img/logo/logo-itergp-txt-right.svg\" alt=\"logo\" width=\"600\" style=\"padding-right: 10px; padding left: 10px;\" title=\"Iterative GP Approximation\"/\u003e\n\u003c/div\u003e\n\u003cbr\u003e\n\n\n\u003cdiv align=\"center\"\u003e\n\n\u003ch4 align=\"center\"\u003e\n  \u003ca href=\"https://itergp.readthedocs.io\"\u003eHome\u003c/a\u003e |\n  \u003ca href=\"https://itergp.readthedocs.io/en/latest/tutorials.html\"\u003eTutorials\u003c/a\u003e |  \n  \u003ca href=\"https://itergp.readthedocs.io/en/latest/api.html\"\u003eAPI Reference\u003c/a\u003e |\n  \u003ca href=\"https://arxiv.org/abs/2205.15449\"\u003eResearch Paper\u003c/a\u003e\n\u003c/h4\u003e\n\n\u003c!-- [![CI build](https://img.shields.io/github/workflow/status/probabilistic-numerics/probnum/Linting?style=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[![PyPI](https://img.shields.io/pypi/v/probnum?style=flat-square\u0026label=PyPI\u0026logo=pypi\u0026logoColor=white)](https://pypi.org/project/probnum/) --\u003e\n\n\u003c/div\u003e\n\n# IterGP: Computation-Aware Gaussian Process Inference\n\nThis repository contains an implementation of the framework described in the paper [Posterior and Computational Uncertainty in Gaussian Processes](https://arxiv.org/abs/2205.15449).\n\n\n## Installation\n\nYou can install the Python package via `pip`:\n\n```bash\npip install git+https://github.com/JonathanWenger/itergp.git\n```\n\n## Documentation and Tutorials\n\nTo understand how to use the functionality of IterGP, take a look at the [API reference](https://itergp.readthedocs.io/en/latest/api.html) and the [tutorials](https://itergp.readthedocs.io/en/latest/tutorials.html).\n\n\n## Datasets\n\nAny datasets used in the experiments can be accessed via the API:\n\n```python\nfrom itergp import datasets\n\ndata = datasets.uci.BikeSharing(dir=\"data/uci\")\ndata.train.y\n# array([ 0.20011634, -2.74432264,  0.14604912, ...,  0.40556032,\n#         0.57590568, -0.54709806])\n```\n\nIf the dataset is not already cached, it will be downloaded and cached locally.\n\n## Citation\n\n```bibtex\n@inproceedings{wenger2022itergp,\n  author    = {Jonathan Wenger and Geoff Pleiss and Marvin Pf{\\\"o}rtner and Philipp Hennig and John P. Cunningham},\n  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},\n  keywords  = {gaussian processes, probabilistic numerics, numerical analysis},\n  title     = {Posterior and Computational Uncertainty in {G}aussian processes},\n  url       = {https://arxiv.org/abs/2205.15449},\n  year      = {2022}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonathanwenger%2Fitergp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjonathanwenger%2Fitergp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonathanwenger%2Fitergp/lists"}