{"id":20307882,"url":"https://github.com/benedekrozemberczki/resolutions-2019","last_synced_at":"2025-04-11T15:12:45.915Z","repository":{"id":102016626,"uuid":"175005943","full_name":"benedekrozemberczki/resolutions-2019","owner":"benedekrozemberczki","description":"A list of data mining and machine learning papers that I implemented in 2019.","archived":false,"fork":false,"pushed_at":"2019-12-28T21:47:17.000Z","size":34,"stargazers_count":21,"open_issues_count":0,"forks_count":10,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-03-25T11:21:34.548Z","etag":null,"topics":["attention-mechanism","deep-learning","deepwalk","gcn","graph-classification","graph-clustering","graph-convolutional-networks","graph-embedding","graph-kernel","machine-learning","network-embedding","network-science","node-classification","node-embedding","node2vec","pytorch","resolution","scipy","sklearn","tensorflow"],"latest_commit_sha":null,"homepage":"","language":null,"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/benedekrozemberczki.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":"2019-03-11T13:28:20.000Z","updated_at":"2024-12-15T08:14:56.000Z","dependencies_parsed_at":null,"dependency_job_id":"5a4763e7-7200-41e6-a727-4382a6b7cf41","html_url":"https://github.com/benedekrozemberczki/resolutions-2019","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/benedekrozemberczki%2Fresolutions-2019","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benedekrozemberczki%2Fresolutions-2019/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benedekrozemberczki%2Fresolutions-2019/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benedekrozemberczki%2Fresolutions-2019/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benedekrozemberczki","download_url":"https://codeload.github.com/benedekrozemberczki/resolutions-2019/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248429118,"owners_count":21101785,"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":["attention-mechanism","deep-learning","deepwalk","gcn","graph-classification","graph-clustering","graph-convolutional-networks","graph-embedding","graph-kernel","machine-learning","network-embedding","network-science","node-classification","node-embedding","node2vec","pytorch","resolution","scipy","sklearn","tensorflow"],"created_at":"2024-11-14T17:19:32.030Z","updated_at":"2025-04-11T15:12:45.901Z","avatar_url":"https://github.com/benedekrozemberczki.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"https://i.imgur.com/thKzPkw.png\"\u003e\n\u003c/div\u003e\n\n## Implementing papers 👨🏻‍💻 ![](https://img.shields.io/badge/progress-46.15%25-green.svg) ![GitHub stars](https://img.shields.io/github/stars/benedekrozemberczki/resolutions-2019.svg?style=plastic) ![GitHub forks](https://img.shields.io/github/forks/benedekrozemberczki/resolutions-2019.svg?color=blue\u0026style=plastic) ![License](https://img.shields.io/github/license/benedekrozemberczki/resolutions-2019.svg?color=blue\u0026style=plastic)\n\nThis year my resolution is that I will implement 52 machine learning papers.\n\n- [x] [1. Graph Classification using Structural Attention](https://github.com/benedekrozemberczki/GAM)\n- [x] [2. Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence](https://github.com/benedekrozemberczki/NMF_ADMM)\n- [x] [3. SINE: Scalable Incomplete Network Embedding](https://github.com/benedekrozemberczki/SINE)\n- [x] [4. Watch Your Step: Learning Graph Embeddings Through Attention](https://github.com/benedekrozemberczki/AttentionWalk)\n- [x] [5. Graph Wavelet Neural Network](https://github.com/benedekrozemberczki/GraphWaveletNeuralNetwork)\n- [x] [6. Biological Network Comparison Using Graphlet Degree Distribution](https://github.com/benedekrozemberczki/OrbitalFeatures)\n- [x] [7. Learning Role-based Graph Embeddings](https://github.com/benedekrozemberczki/role2vec)\n- [x] [8. SimGNN: A Neural Network Approach to Fast Graph Similarity Computation](https://github.com/benedekrozemberczki/SimGNN)\n- [x] [9. Predict then Propagate: Graph Neural Networks meet Personalized PageRank](https://github.com/benedekrozemberczki/APPNP)\n- [x] [10. A Higher Order Graph Convolutional Network](https://github.com/benedekrozemberczki/MixHop-and-N-GCM)\n- [x] [11. Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters](https://github.com/benedekrozemberczki/EgoSplitting)\n- [x] [12. Splitter: Learning Node Representations that Capture Multiple Social Contexts](https://github.com/benedekrozemberczki/Splitter)\n- [x] [13. Capsule Graph Neural Network](https://github.com/benedekrozemberczki/CapsGNN)\n- [x] [14. GEMSEC: Graph Embedding With Self-Clustering](https://github.com/benedekrozemberczki/GEMSEC)\n- [x] [15. Jump Around! Multi-scale Attributed Node Embedding](https://github.com/benedekrozemberczki/MUSAE)\n- [x] [16. Semi-Supervised Graph Classification: A Hierarchical Graph Perspective](https://github.com/benedekrozemberczki/SEAL)\n- [x] [17. MixHop: Higher-Order Graph Convolutional Architecturesvia Sparsified Neighborhood Mixing](https://github.com/benedekrozemberczki/MixHop-and-N-GCN)\n- [x] [18. GraRep: Learning Graph Representations with Global Structural Information](https://github.com/benedekrozemberczki/GraRep)\n- [x] [19. Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks](https://github.com/benedekrozemberczki/ClusterGCN)\n- [x] [20. EdMot: An Edge Enhancement Approach for Motif-aware Community Detection](https://github.com/benedekrozemberczki/EdMot)\n- [x] [21. Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation](https://github.com/benedekrozemberczki/BoostedFactorization)\n- [x] [22. A Non-negative Symmetric Encoder-Decoder Approach\n    for Community Detection](https://github.com/benedekrozemberczki/karateclub)\n- [x] [23. Multi-scale Attributed Node Embedding](https://github.com/benedekrozemberczki/MUSAE)\n- [x] [24. Overlapping Community Detection at Scale: A Nonnegative Matrix Factorization Approach](https://github.com/benedekrozemberczki/karateclub)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenedekrozemberczki%2Fresolutions-2019","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenedekrozemberczki%2Fresolutions-2019","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenedekrozemberczki%2Fresolutions-2019/lists"}