{"id":13717098,"url":"https://github.com/t-vi/candlegp","last_synced_at":"2025-09-03T01:38:59.548Z","repository":{"id":83673036,"uuid":"108037443","full_name":"t-vi/candlegp","owner":"t-vi","description":"Gaussian Processes in Pytorch","archived":false,"fork":false,"pushed_at":"2020-02-26T16:38:00.000Z","size":2748,"stargazers_count":75,"open_issues_count":0,"forks_count":8,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-07-08T20:45:41.055Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/t-vi.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":"2017-10-23T20:45:51.000Z","updated_at":"2024-12-11T03:03:04.000Z","dependencies_parsed_at":"2023-05-06T18:31:49.095Z","dependency_job_id":null,"html_url":"https://github.com/t-vi/candlegp","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/t-vi/candlegp","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t-vi%2Fcandlegp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t-vi%2Fcandlegp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t-vi%2Fcandlegp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t-vi%2Fcandlegp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/t-vi","download_url":"https://codeload.github.com/t-vi/candlegp/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/t-vi%2Fcandlegp/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273377150,"owners_count":25094526,"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","status":"online","status_checked_at":"2025-09-02T02:00:09.530Z","response_time":77,"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":[],"created_at":"2024-08-03T00:01:17.908Z","updated_at":"2025-09-03T01:38:59.512Z","avatar_url":"https://github.com/t-vi.png","language":"Jupyter Notebook","funding_links":[],"categories":["Pytorch \u0026 related libraries｜Pytorch \u0026 相关库","Pytorch \u0026 related libraries"],"sub_categories":["Other libraries｜其他库:","Other libraries:"],"readme":"# CandleGP - Gaussian Processes in Pytorch\n*Thomas Viehmann*, tv@lernapparat.de\n\n*Note:* This stems from before the Tensor/Variable merge, so it is really old.\nI recently needed bits and ported those to PyTorch 1.4, but there are rough edges w.r.t. dimensionality of quantities and there will be unported bits.\n\n\nI felt Bayesian the other day, so I ported (a tiny part of) the\nexcellent [GPFlow library](https://github.com/gpflow/gpflow) to\nPytorch.\n\nI have kept the structure close to GPFlow.\nMost of the great ideas are from the GPFlow team, errors are my own.\n\nThe functionality is demonstrated by the following notebooks\nadapted from gpflow:\n\n- [Classification example](notebooks/classification.ipynb)\n- [Regression example](notebooks/gp_regression.ipynb)\n- [Markov Chain Monte Carlo for non-gaussian likelihoods](notebooks/mcmc.ipynb)\n- [Upper bound for variational inference](notebooks/upper_bound.ipynb)\n- [SVGP with minibatch training](notebooks/minibatches.ipynb)\n- [Multi-class classification](notebooks/multiclass.ipynb)\n\nTodo:\n- GPLVM\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ft-vi%2Fcandlegp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ft-vi%2Fcandlegp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ft-vi%2Fcandlegp/lists"}