{"id":31799513,"url":"https://github.com/mims-harvard/graphml-tutorials","last_synced_at":"2025-10-10T22:02:34.836Z","repository":{"id":42199905,"uuid":"275182202","full_name":"mims-harvard/graphml-tutorials","owner":"mims-harvard","description":"Tutorials for Machine Learning on Graphs","archived":false,"fork":false,"pushed_at":"2021-07-08T09:24:51.000Z","size":59151,"stargazers_count":195,"open_issues_count":0,"forks_count":52,"subscribers_count":9,"default_branch":"master","last_synced_at":"2024-03-26T02:22:12.094Z","etag":null,"topics":["deep-learning","embeddings","graph-convolutional-networks","graph-ml","graph-neural-networks","network-embeddings","networks","representation-learning","tutorials"],"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/mims-harvard.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":"2020-06-26T15:00:38.000Z","updated_at":"2024-03-25T14:29:40.000Z","dependencies_parsed_at":"2022-08-16T04:30:29.091Z","dependency_job_id":null,"html_url":"https://github.com/mims-harvard/graphml-tutorials","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mims-harvard/graphml-tutorials","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mims-harvard%2Fgraphml-tutorials","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mims-harvard%2Fgraphml-tutorials/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mims-harvard%2Fgraphml-tutorials/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mims-harvard%2Fgraphml-tutorials/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mims-harvard","download_url":"https://codeload.github.com/mims-harvard/graphml-tutorials/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mims-harvard%2Fgraphml-tutorials/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279005433,"owners_count":26083891,"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":"2025-10-10T02:00:06.843Z","response_time":62,"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":["deep-learning","embeddings","graph-convolutional-networks","graph-ml","graph-neural-networks","network-embeddings","networks","representation-learning","tutorials"],"created_at":"2025-10-10T22:02:29.109Z","updated_at":"2025-10-10T22:02:34.831Z","avatar_url":"https://github.com/mims-harvard.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Tutorials for Machine Learning on Graphs\n\n![GitHub Workflow Status](https://img.shields.io/github/workflow/status/mims-harvard/graphml-tutorials/Run%20Dependency%20Test?logo=Python\u0026logoColor=%23EE4C2C\u0026style=flat)\n\n## Contributors\n\n- Payal Chandak (chandak@mit.edu)\n- Haoxin Li (haoxin_li@hsph.harvard.edu)\n- Min Jean Cho (min_jean_cho@brown.edu)\n- Pavlin Policar (pavlin.policar@fri.uni-lj.si)\n- Mert Erden (mert.erden@tufts.edu)\n- Steffan Paul (steffanpaul@g.harvard.edu)\n- Marinka Zitnik (marinka@hms.harvard.edu)\n\n## Overview\n\nGraph machine learning provides a powerful toolbox to learn representations from any arbitrary graph structure and use learned representations for a variety of downstream tasks. These tutorials aim to:\n\n1. Introduce the concept of graph neural networks (GNNs).\n2. Discuss the theoretical motivation behind different GNN architectures.\n3. Provide implementations of these architectures.\n4. Apply the architectures to key prediction problems on interconnected data in science and medicine.\n5. Provide end-to-end real-world examples of graph machine learning.\n\n![graph-ML](./graphML.png)\n\n## Requirements\n\nRecent versions of NumPy, PyTorch, PyTorch Geometric and Jupyter are required. \n\n## Installation\n\nAll the required packages can be installed using the following commands:\n\n1. `git clone https://github.com/mims-harvard/graphml-tutorials.git`\n2. `cd graphml-tutorials`\n3. `chmod +x install.sh \u0026\u0026 ./install.sh`\n4. `conda activate graphml_venv`\n\n## Contributing\n\nPull requests are welcome.\n\n## License\n\n[MIT](https://choosealicense.com/licenses/mit/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmims-harvard%2Fgraphml-tutorials","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmims-harvard%2Fgraphml-tutorials","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmims-harvard%2Fgraphml-tutorials/lists"}