{"id":13526057,"url":"https://github.com/tonysy/awesome-graph-networks","last_synced_at":"2026-01-22T17:02:27.176Z","repository":{"id":96964840,"uuid":"139246831","full_name":"tonysy/awesome-graph-networks","owner":"tonysy","description":"Materials for Graph Models and Graph Networks","archived":false,"fork":false,"pushed_at":"2018-07-06T15:22:23.000Z","size":24823,"stargazers_count":10,"open_issues_count":0,"forks_count":1,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-05-21T08:33:52.380Z","etag":null,"topics":["artificial-intelligence","deep-learning","probabilistic-graphical-models"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tonysy.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2018-06-30T12:14:33.000Z","updated_at":"2020-12-30T03:49:57.000Z","dependencies_parsed_at":"2024-01-12T17:34:26.087Z","dependency_job_id":"10535abb-9e9c-4a76-9008-135fdef73f9f","html_url":"https://github.com/tonysy/awesome-graph-networks","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/tonysy%2Fawesome-graph-networks","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tonysy%2Fawesome-graph-networks/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tonysy%2Fawesome-graph-networks/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tonysy%2Fawesome-graph-networks/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tonysy","download_url":"https://codeload.github.com/tonysy/awesome-graph-networks/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247871105,"owners_count":21009986,"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":["artificial-intelligence","deep-learning","probabilistic-graphical-models"],"created_at":"2024-08-01T06:01:24.764Z","updated_at":"2026-01-22T17:02:22.097Z","avatar_url":"https://github.com/tonysy.png","language":null,"funding_links":[],"categories":["Uncategorized"],"sub_categories":["Uncategorized"],"readme":"# Awesome-Graph-Networks\n[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/sindresorhus/awesome)\n\nMaterials for Graph Models and Graph Networks\n## 1. Probabilistic Graph Models\n- [(Stanford)CS 228: Probabilistic Graphical Models](https://cs.stanford.edu/~ermon/cs228/index.html)\n    - [[Slides]](https://ermongroup.github.io/cs228-notes/)\n    - [[Videos]](https://www.youtube.com/playlist?list=PLBAGcD3siRDjiQ5VZQ8t0C7jkHQ8fhuq8)\n- [(Coursera)Probabilistic Graphical Models](https://www.coursera.org/learn/probabilistic-graphical-models/)\n    - [[Slides]](./Course/coursera_probabilistic_graphical_models/slides)\n\n- [(CMU)Probabilistic Graphical Models](http://www.cs.cmu.edu/~epxing/Class/10708/lecture.html)\n    - Slides are in course homepage\n    - [[Videos]](https://www.youtube.com/playlist?list=PLI3nIOD-p5aoXrOzTd1P6CcLavu9rNtC-)\n## 2. Graph Neural Networks\n### (1) Blogs\n- [GRAPH CONVOLUTIONAL NETWORKS](http://tkipf.github.io/graph-convolutional-networks/)\nA good blog to introduce graph covolutional network\n\n### (2) Papers\n- [Relational inductive biases, deep learning, and graph networks(recommend to read first)](https://arxiv.org/pdf/1806.01261.pdf) \n- [Semi-Supervised Classification with Graph Convolutional Networks(ICLR 2017)](http://arxiv.org/abs/1609.02907)\n- [Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering (NIPS 2016)](https://arxiv.org/abs/1606.09375)\n\n- [Graph Attention Networks (ICLR 2018)](https://arxiv.org/pdf/1710.10903.pdf)\n- [Few-shot Learning with Graph Neural Networks (ICLR 2018)](https://arxiv.org/pdf/1711.04043.pdf)\n\n## 3. Comments\n### (1) Spectral Approach\nWhich works with a spectral representations of the graph and have been successfully applied in the context of node classification.\n### (2) Non-spectral Approach\nWhich define convolutions directly on the graph, operating on groups of spatially close neighbors.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftonysy%2Fawesome-graph-networks","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftonysy%2Fawesome-graph-networks","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftonysy%2Fawesome-graph-networks/lists"}