{"id":19382171,"url":"https://github.com/codito/obliviate","last_synced_at":"2026-05-16T04:03:34.551Z","repository":{"id":66523112,"uuid":"365928625","full_name":"codito/obliviate","owner":"codito","description":"A collection of algorithms to model memory and forgetfulness","archived":false,"fork":false,"pushed_at":"2021-05-14T12:15:54.000Z","size":37,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-01-07T06:41:50.641Z","etag":null,"topics":["bayesian-statistics","memory","quiz","retention","spaced-repetition","statistical-methods"],"latest_commit_sha":null,"homepage":"","language":"C#","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/codito.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","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":"2021-05-10T05:32:12.000Z","updated_at":"2021-05-14T12:15:56.000Z","dependencies_parsed_at":"2023-02-28T01:01:27.693Z","dependency_job_id":null,"html_url":"https://github.com/codito/obliviate","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codito%2Fobliviate","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codito%2Fobliviate/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codito%2Fobliviate/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/codito%2Fobliviate/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/codito","download_url":"https://codeload.github.com/codito/obliviate/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240518965,"owners_count":19814514,"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-statistics","memory","quiz","retention","spaced-repetition","statistical-methods"],"created_at":"2024-11-10T09:19:55.111Z","updated_at":"2026-05-16T04:03:34.450Z","avatar_url":"https://github.com/codito.png","language":"C#","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Obliviate\n\nA collection of algorithms to model memory and retention of facts.\n\n[![Build Status](https://github.com/spekt/testlogger/workflows/.NET/badge.svg)](https://github.com/spekt/testlogger/actions?query=workflow%3A.NET)\n[![NuGet](https://img.shields.io/nuget/v/Obliviate.svg)](https://www.nuget.org/packages/Obliviate/)\n\n\u003c!--\n[![NuGet Downloads](https://img.shields.io/nuget/dt/Obliviate)](https://www.nuget.org/packages/Obliviate/)\n--\u003e\n\n## Usage\n\nInstall the nuget package in your project with `dotnet add package obliviate`.\n\n### Ebisu\n\nEbisu provides a simple model that must be attached with each _fact_ the user is\ntrying to memorise. See the notes on [EbisuModel][] on choosing the parameters.\n\nA learning/quizzing app will need to store the model, schedule reviews and keep\nit fresh with observations from each review session. Ebisu provides two primary\nAPIs for these tasks. First, [PredictRecall][] attempts to find recall\nprobability of the existing model at a given time. E.g. _will I remember this\nfact after X time units from the last review?_ Second, assume we reviewed the\nfact `n` times with `k` successful reviews after `t` time units from last\nreview. [UpdateRecall][] updates the previous model with these additional\nobservations.\n\nEbisu provides fantastic documentation [here][ebisu]. We highly recommend a read\nif you're planning to use the algorithm.\n\n[ebisumodel]: https://github.com/codito/obliviate/blob/master/src/Obliviate/Ebisu/EbisuModel.cs\n[predictrecall]: https://github.com/codito/obliviate/blob/54e74e55fd27bd4681c94bef8c60acd5f90aaabd/src/Obliviate/Ebisu/EbisuModelExtensions.cs#L29\n[updaterecall]: https://github.com/codito/obliviate/blob/54e74e55fd27bd4681c94bef8c60acd5f90aaabd/src/Obliviate/Ebisu/EbisuModelExtensions.cs#L68\n[ebisu]: https://fasiha.github.io/ebisu/\n\n## Algorithms\n\n- [x] Ebisu: https://fasiha.github.io/ebisu/ v2.0.0 (Public domain)\n  - [ ] Ebisu v2.1.0 support with soft binary quizzes and half life rescale\n- [ ] Memorize: https://github.com/Networks-Learning/memorize (MIT)\n- [ ] Duolingo Halflife: https://github.com/duolingo/halflife-regression (MIT)\n- [ ] SM-2 and related family of algorithms\n\nWe plan to support these algorithms along with benchmarks in future. Contributions\nand suggestions are most welcome!\n\n## License\n\nMIT\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodito%2Fobliviate","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcodito%2Fobliviate","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodito%2Fobliviate/lists"}