{"id":13483542,"url":"https://github.com/aniket-agarwal1999/vGraph-Pytorch","last_synced_at":"2025-03-27T14:31:27.306Z","repository":{"id":183414233,"uuid":"213923202","full_name":"aniket-agarwal1999/vGraph-Pytorch","owner":"aniket-agarwal1999","description":"Implementation of the paper \"vGraph: A Generative Model For Joint Community Detection and Node Representational Learning\" under NeurIPS Reproducibility challenge 2019","archived":false,"fork":false,"pushed_at":"2019-12-02T20:12:21.000Z","size":1638,"stargazers_count":8,"open_issues_count":0,"forks_count":3,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-10-30T17:47:57.589Z","etag":null,"topics":["deep-learning","graphical-models","nips-2019","pytorch","representation-learning"],"latest_commit_sha":null,"homepage":"","language":"Python","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/aniket-agarwal1999.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}},"created_at":"2019-10-09T13:15:24.000Z","updated_at":"2022-03-03T01:28:01.000Z","dependencies_parsed_at":null,"dependency_job_id":"cd54897e-b591-431f-bf53-4ba2a1a43339","html_url":"https://github.com/aniket-agarwal1999/vGraph-Pytorch","commit_stats":null,"previous_names":["aniket-agarwal1999/vgraph-pytorch"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aniket-agarwal1999%2FvGraph-Pytorch","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aniket-agarwal1999%2FvGraph-Pytorch/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aniket-agarwal1999%2FvGraph-Pytorch/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/aniket-agarwal1999%2FvGraph-Pytorch/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/aniket-agarwal1999","download_url":"https://codeload.github.com/aniket-agarwal1999/vGraph-Pytorch/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245863097,"owners_count":20684787,"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":["deep-learning","graphical-models","nips-2019","pytorch","representation-learning"],"created_at":"2024-07-31T17:01:12.544Z","updated_at":"2025-03-27T14:31:26.335Z","avatar_url":"https://github.com/aniket-agarwal1999.png","language":"Python","funding_links":[],"categories":["Factorization"],"sub_categories":[],"readme":"# vGraph: A Generative Model For Joint Community Detection and Node Representational Learning\n\nThis is a Pytorch implementation of the paper [vGraph: A Generative Model For Joint Community Detection and Node Representational Learning](https://arxiv.org/abs/1906.07159) and is done under the **NeurIPS Reproducibility Challenge 2019**. The original implementation by author can be found [here](https://github.com/fanyun-sun/vGraph).\n\n## Summary of the paper\n\n\u003cimg src='https://github.com/aniket-agarwal1999/vGraph-Pytorch/blob/master/images/model.png'\u003e\n\nThis paper proposes a novel technique for learning node representations and at the same time perform community detection task for the graphical data by creating a generative model using the variational inference concepts. **The full paper summary along with its main contributions can be found [here](https://github.com/vlgiitr/papers_we_read/blob/master/summaries/vgraph.md)**\n\n## Setup Instructions and Dependancies\n\nThe code has been written in *Python 3.6* and *Pytorch v1.1*. Also Pytorch Geometric has been used for training procedures, along with the usage of TensorboardX for logging loss curves.\n\nFor training/testing the model, you must first download `Facebook social circles` dataset. It can be found [here](https://snap.stanford.edu/data/ego-Facebook.html). After downloading the dataset, all the files must be placed inside `./dataset/Facebook/`.\n\n## Repository Overview\n\nThe following is the information regarding the various important files in the directory and their functions:\n\n- `model.py`: File containing the network architecture\n- `utils.py`: File containing helper functions and losses\n- `data.py`: File containing functions to call dataset in an operable format\n- `train_nonoverlapping.py`: File containing the training procedure for non-overlapping dataset\n- `train_overlapping.py`: File containing the training procedure for overlapping dataset\n\n## Running the model\n\nFor training the model, use the following commands:\n\n```\npython train_nonoverlapping.py            ### For training non-overlapping dataset\npython train_overlapping.py               ### For training overlapping dataset\n```\n\n## Current Status of the Project\n\nCurrently the directory contains dataloader and training procedure for 2 non-overlapping datasets(`Cora` and `Citeseer`) and 10 overlapping datasets(`facebook0`, `facebook107`, `facebook1684`, `facebook1912`, `facebook3437`, `facebook348`, `facebook3980`, `facebook414`, `facebook686`, `facebook698`). I plan to add more dataloaders in the directory. Also the various accuracy measures as specified in the paper will also soon be added in the repository.\n\n```\nIf you found the codebase useful in your research work, consider citing the original paper\n```\n\n## License\n\nThis repository is licensed under MIT License","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faniket-agarwal1999%2FvGraph-Pytorch","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Faniket-agarwal1999%2FvGraph-Pytorch","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Faniket-agarwal1999%2FvGraph-Pytorch/lists"}