{"id":26962554,"url":"https://github.com/nickhnelsen/error-bounds-for-vvrf","last_synced_at":"2026-08-07T21:03:27.252Z","repository":{"id":196739308,"uuid":"673945491","full_name":"nickhnelsen/error-bounds-for-vvRF","owner":"nickhnelsen","description":"Code for the paper ``Error Bounds for Learning with Vector-Valued Random Features'' (NeurIPS 2023, Spotlight)","archived":false,"fork":false,"pushed_at":"2024-08-08T11:38:45.000Z","size":78,"stargazers_count":3,"open_issues_count":1,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-16T18:26:00.861Z","etag":null,"topics":["fourier-neural-operator","functional-regression","infinite-dimensions","neural-operator","operator-learning","partial-differential-equations","random-features"],"latest_commit_sha":null,"homepage":"https://proceedings.neurips.cc/paper_files/paper/2023/hash/e34d908241aef40440e61d2a27715424-Abstract-Conference.html","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/nickhnelsen.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":"2023-08-02T19:30:38.000Z","updated_at":"2025-02-27T07:45:38.000Z","dependencies_parsed_at":"2024-04-25T23:55:03.999Z","dependency_job_id":"e3139a99-3b4e-4348-8b55-6a16be72f7e7","html_url":"https://github.com/nickhnelsen/error-bounds-for-vvRF","commit_stats":null,"previous_names":["nickhnelsen/error-bounds-for-vvrf"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/nickhnelsen/error-bounds-for-vvRF","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickhnelsen%2Ferror-bounds-for-vvRF","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickhnelsen%2Ferror-bounds-for-vvRF/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickhnelsen%2Ferror-bounds-for-vvRF/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickhnelsen%2Ferror-bounds-for-vvRF/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/nickhnelsen","download_url":"https://codeload.github.com/nickhnelsen/error-bounds-for-vvRF/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/nickhnelsen%2Ferror-bounds-for-vvRF/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":36389942,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-08-06T04:43:03.162Z","status":"online","status_checked_at":"2026-08-07T02:00:06.708Z","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":["fourier-neural-operator","functional-regression","infinite-dimensions","neural-operator","operator-learning","partial-differential-equations","random-features"],"created_at":"2025-04-03T05:28:47.177Z","updated_at":"2026-08-07T21:03:27.220Z","avatar_url":"https://github.com/nickhnelsen.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Code for the 2023 NeurIPS Spotlight paper ``Error Bounds for Learning with Vector-Valued Random Features''\n\n## Installation\nThe command\n```\nconda env create -f Project.yml\n```\ncreates an environment called ``operator``. [PyTorch](https://pytorch.org/) will be installed in this step.\n\nActivate the environment with\n```\nconda activate operator\n```\nand deactivate with\n```\nconda deactivate\n```\n\n\n## Data\nThe 1D viscous Burgers' equation dataset is a standard operator learning benchmark first introduced in [Nelsen and Stuart 2021](https://arxiv.org/abs/2005.10224).\n\nThe particular setup used in this example comes from [zongyi-li/fourier_neural_operator](https://github.com/zongyi-li/fourier_neural_operator) and is found below:\n\n* [Burgers' dataset](https://drive.google.com/drive/folders/1UnbQh2WWc6knEHbLn-ZaXrKUZhp7pjt-?usp=sharing)\n\nPlease download ``Burgers_R10.zip`` which contains the dataset file ``burgers_data_R10.mat``. There are $2048$ input-outpairs at spatial resolution $8192$.\n\n## Running the example\nIn the script ``train.py``, assign in the variable ``data_path`` the global path to the data file ``burgers_data_R10.mat``.\n\nThe example may then be run as\n```\npython -u train.py M N J 0 lambda my_path\n```\nwhere\n* ``M`` is the number of random features,\n* ``N`` is the number of training data pairs,\n* ``J`` is the desired spatial resolution for training and testing.\n* ``lambda`` is the regularization parameter\n* ``my_path`` is the output directory\n\nThe code defaults to running on GPU, if one is available.\n\n## References\n- [Error Bounds for Learning with Vector-Valued Random Features](https://arxiv.org/abs/2305.17170)\n- [The Random Feature Model for Input-Output Maps between Banach Spaces](https://arxiv.org/abs/2005.10224)\n- [Fourier Neural Operator for Parametric Partial Differential Equations](https://arxiv.org/abs/2010.08895)\n- [Operator Learning Using Random Features: A Tool for Scientific Computing](https://doi.org/10.1137/24M1648703)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnickhnelsen%2Ferror-bounds-for-vvrf","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnickhnelsen%2Ferror-bounds-for-vvrf","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnickhnelsen%2Ferror-bounds-for-vvrf/lists"}