{"id":18538159,"url":"https://github.com/emilemathieu/ntl.jl","last_synced_at":"2026-01-23T05:37:30.780Z","repository":{"id":75412848,"uuid":"117692460","full_name":"emilemathieu/NTL.jl","owner":"emilemathieu","description":"Code for UAI paper « Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks »","archived":false,"fork":false,"pushed_at":"2018-08-02T10:08:52.000Z","size":27,"stargazers_count":4,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-07-25T07:56:18.656Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://arxiv.org/abs/1807.03113","language":"Julia","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/emilemathieu.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":"2018-01-16T14:16:45.000Z","updated_at":"2022-02-25T05:19:36.000Z","dependencies_parsed_at":null,"dependency_job_id":"7bf1ae4f-be75-4195-a524-cb08b26885eb","html_url":"https://github.com/emilemathieu/NTL.jl","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/emilemathieu/NTL.jl","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/emilemathieu%2FNTL.jl","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/emilemathieu%2FNTL.jl/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/emilemathieu%2FNTL.jl/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/emilemathieu%2FNTL.jl/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/emilemathieu","download_url":"https://codeload.github.com/emilemathieu/NTL.jl/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/emilemathieu%2FNTL.jl/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28681017,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-23T04:33:33.518Z","status":"ssl_error","status_checked_at":"2026-01-23T04:33:30.433Z","response_time":59,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":"2024-11-06T19:42:32.466Z","updated_at":"2026-01-23T05:37:30.751Z","avatar_url":"https://github.com/emilemathieu.png","language":"Julia","funding_links":[],"categories":[],"sub_categories":[],"readme":"# NTL.jl\nCode to accompany UAI 2018 paper ['Sampling and Inference for Beta Neutral-to-the-Left Models of Sparse Networks'](http://auai.org/uai2018/proceedings/papers/185.pdf)  ([supplement](http://auai.org/uai2018/proceedings/supplements/Supplementary-Paper185.pdf)).\n\n## Data\n\n### SNAP datasets\n\nThe [Stanford Large Network Dataset Collection](https://snap.stanford.edu/data/#temporal) contains a number of interesting temporal networks.\nWe recommend preprocessing the datasets as follows:\n\n    wget https://snap.stanford.edu/data/$NAME.txt.gz\n    gunzip $NAME.txt.gz\n    sort -k3 -n $NAME.txt \u003e sorted-$NAME.txt\n\n\n## Maximum likelihood parameter estimation\n\nSee `examples/mle.jl` for an example of computing MLEs on massive datasets.\n\n\n## Gibbs sampling arrival order, arrival times, parameters\n\nSee `examples/gibbs.jl` for an example of performing posterior inference over parameters\nand latent variables on datasets of modest size (e.g., hundreds or thousands of nodes).\nThe code can be run interactively (i.e., section by section) or as a script\nfrom the Julia REPL or command line.\n\nSee `examples/gibbs_plots.jl` for some example plots for assessing sampler output.\n\nSee `examples/gibbs_ess_experiments.jl` for code used to produce the tables in Section 5.1\nof the paper.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Femilemathieu%2Fntl.jl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Femilemathieu%2Fntl.jl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Femilemathieu%2Fntl.jl/lists"}