{"id":20539503,"url":"https://github.com/lestherll/gnns","last_synced_at":"2025-10-24T05:48:40.602Z","repository":{"id":207483797,"uuid":"608428193","full_name":"lestherll/GNNs","owner":"lestherll","description":"Notes for learning GNNS","archived":false,"fork":false,"pushed_at":"2023-03-06T20:29:13.000Z","size":6738,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-16T14:45:56.387Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter 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Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Graph Neural Network (GNN) Notes\n\nCollection of notebooks, scripts, and resources for learning GNNs.\n\n## Resources\n\n### Courses\n- [CS224W: Machine Learning with Graphs (Winter 2023)](http://web.stanford.edu/class/cs224w/) by Stanford University\n- [ESE 5140: Graph Neural Networks (Fall 2020)](https://gnn.seas.upenn.edu/)  by University of Pennsylvania \n- [COMP 776: Graph Representation Learning (Winter 2020)](https://cs.mcgill.ca/~wlh/comp766/syllabus.html) by Hamilton\n- [Graph Neural Network Course](https://github.com/mlabonne/graph-neural-network-course) by Labonne\n\n### Books\n- [Graph Neural Networks](https://graph-neural-networks.github.io/) by Wu et al.\n- [Graph Representation Learning](https://www.cs.mcgill.ca/~wlh/grl_book/) by Hamilton\n\n### Papers\n- [Semi-Supervised Classification with Graph Convolutional Networks](https://arxiv.org/pdf/1609.02907.pdf) by Kipf and Welling\n- [How Powerful are Graph Neural Networks](https://arxiv.org/pdf/1810.00826.pdf) by Xu et al.\n- [DeepWalk: Online Learning of Social Representations](https://arxiv.org/pdf/1403.6652.pdf) by Perozzi et al.\n- [node2vec: Scalable Feature Learning for Networks](https://arxiv.org/pdf/1607.00653.pdf) by Grover and Leskovec\n- [Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec](https://arxiv.org/pdf/1710.02971.pdf) by Qiu et al.\n- [Graph Neural Networks: A Review of Methods and Applications](https://arxiv.org/pdf/1812.08434.pdf) by Zhou et al.\n- [A Practical Tutorial on Graph Neural Network](https://arxiv.org/pdf/2010.05234.pdf) by Ward et al.\n- \n\n### Blogs\n- [Thomas Kipf](https://tkipf.github.io/graph-convolutional-networks/)\n- [A Gentle Introduction to Graph Neural Networks](https://distill.pub/2021/gnn-intro/)\n- [Understanding Convolutions on Graphs](https://distill.pub/2021/understanding-gnns/)\n- [A Comprehensive Introduction to Graph Neural Networks (GNNs)](https://www.datacamp.com/tutorial/comprehensive-introduction-graph-neural-networks-gnns-tutorial)\n\n\n### Repos\n- [Awesome Graph Neural Networks](https://github.com/GRAND-Lab/Awesome-Graph-Neural-Networks)\n- [GNNPapers](https://github.com/thunlp/GNNPapers)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flestherll%2Fgnns","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flestherll%2Fgnns","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flestherll%2Fgnns/lists"}