{"id":18985035,"url":"https://github.com/dobraczka/gnntutorial","last_synced_at":"2025-04-19T20:26:12.729Z","repository":{"id":117525210,"uuid":"568882974","full_name":"dobraczka/GNNTutorial","owner":"dobraczka","description":"A small tutorial notebook on Graph Neural Networks, especially Graph Convolutional Networks","archived":false,"fork":false,"pushed_at":"2022-11-23T12:52:01.000Z","size":21560,"stargazers_count":17,"open_issues_count":0,"forks_count":5,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-04-16T19:21:41.042Z","etag":null,"topics":["gat","gcn","graph-convolutional-networks","graph-neural-networks","rgcn"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/dobraczka.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":"2022-11-21T16:01:14.000Z","updated_at":"2025-04-16T08:59:43.000Z","dependencies_parsed_at":null,"dependency_job_id":"9cd756e2-901f-44b5-a5a0-2296fb708aee","html_url":"https://github.com/dobraczka/GNNTutorial","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dobraczka%2FGNNTutorial","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dobraczka%2FGNNTutorial/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dobraczka%2FGNNTutorial/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dobraczka%2FGNNTutorial/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dobraczka","download_url":"https://codeload.github.com/dobraczka/GNNTutorial/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249793729,"owners_count":21326578,"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":["gat","gcn","graph-convolutional-networks","graph-neural-networks","rgcn"],"created_at":"2024-11-08T16:24:10.108Z","updated_at":"2025-04-19T20:26:12.711Z","avatar_url":"https://github.com/dobraczka.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# An intro to Graph Neural Networks 🕸️🧠\n\nGraph Neural Networks have seen a rise in popularity. This is no surprise since various forms of information can be understood in the context of graphs from social networks to molecules.\nThis notebook intends to illuminate the inner workings of [Graph Convolutional Networks](https://arxiv.org/abs/1609.02907) and give an intuition into some other types of Networks which extend this idea.\n\n# Environment and Kernel Setup\n\nIf you work on the clara/paula cluster [load](https://www.sc.uni-leipzig.de/user-doc/quickstart/hpc/#use-preinstalled-software) python:\n```\nml Python/3.9.5-GCCcore-10.3.0\n```\nor Anaconda\n\n```\nml Anaconda3/2021.11\n```\n\nand then create the environment with the respective dependencies:\n\n```\nconda env create n \"PyG\" -f environment.yml\n```\n\nActivate the environment\n\n```\nconda activate PyG\n``` \n\nNow create a kernel to use in the Jupyter Notebook\n\n```\nipython kernel install --user --name \"PyG\" --display-name \"PyG\"\n```\n\nNow you can go to the JupyterLab, select the kernel `PyG` and run the notebook.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdobraczka%2Fgnntutorial","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdobraczka%2Fgnntutorial","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdobraczka%2Fgnntutorial/lists"}