{"id":21280660,"url":"https://github.com/borgwardtlab/ggme","last_synced_at":"2025-07-11T10:32:41.125Z","repository":{"id":40772836,"uuid":"463462032","full_name":"BorgwardtLab/ggme","owner":"BorgwardtLab","description":"Official repository for the ICLR 2022 paper \"Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions\" https://openreview.net/forum?id=tBtoZYKd9n","archived":false,"fork":false,"pushed_at":"2022-07-05T18:45:03.000Z","size":356,"stargazers_count":12,"open_issues_count":0,"forks_count":0,"subscribers_count":5,"default_branch":"main","last_synced_at":"2023-06-09T12:05:13.346Z","etag":null,"topics":["evaluation-framework","evaluation-metrics","generative-model","graph-learning","machine-learning"],"latest_commit_sha":null,"homepage":"https://openreview.net/pdf?id=tBtoZYKd9n","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BorgwardtLab.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}},"created_at":"2022-02-25T08:52:18.000Z","updated_at":"2023-06-01T12:55:31.000Z","dependencies_parsed_at":"2022-07-09T11:00:27.992Z","dependency_job_id":null,"html_url":"https://github.com/BorgwardtLab/ggme","commit_stats":null,"previous_names":[],"tags_count":null,"template":null,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2Fggme","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2Fggme/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2Fggme/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2Fggme/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BorgwardtLab","download_url":"https://codeload.github.com/BorgwardtLab/ggme/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225715644,"owners_count":17512906,"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":["evaluation-framework","evaluation-metrics","generative-model","graph-learning","machine-learning"],"created_at":"2024-11-21T10:38:14.725Z","updated_at":"2024-11-21T10:38:15.308Z","avatar_url":"https://github.com/BorgwardtLab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ggme: \u003cu\u003eG\u003c/u\u003eraph \u003cu\u003eG\u003c/u\u003eenerative \u003cu\u003eM\u003c/u\u003eodel \u003cu\u003eE\u003c/u\u003evaluation\nThis is the official repository for the ICLR 2022 paper \"Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions\" https://openreview.net/forum?id=tBtoZYKd9n\n\n# Dependencies\n\nDependencies are managed using `poetry.` To setup the environment,\nplease run `poetry install` from the main directory (assuming the user\nalready has installed `poetry`).\n\n# Running ggme\n\nThe primary script is contained in `main.py`. We assume that the user\nhas two distributions which they would like to compare using MMD, given\na specified kernel and descriptor function. \n\nWe assume that each distribution of graphs is stored as a list of `networkx`\ngraphs. \n\n# Example script  \n\nWe provide an example run in `main.py` based on predictions of a graph\ngenerative model and the graphs in the corresponding test set. To run\nthis, execute the following code from the main directory.\n\n```shell  \ncd src\npoetry run python main.py\n```\n\n# Citing our work\n\nPlease consider citing our work: \n\n```bibtex\n@inproceedings{obray2022evaluation,\n\ttitle        = {Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions},\n\tauthor       = {Leslie O'Bray and Max Horn and Bastian Rieck and Karsten Borgwardt},\n\tyear         = 2022,\n\tbooktitle    = {International Conference on Learning Representations},\n\turl          = {https://openreview.net/forum?id=tBtoZYKd9n}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborgwardtlab%2Fggme","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fborgwardtlab%2Fggme","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborgwardtlab%2Fggme/lists"}