{"id":13678296,"url":"https://github.com/tadpole/DRNE","last_synced_at":"2025-04-29T12:34:39.081Z","repository":{"id":75945188,"uuid":"155543504","full_name":"tadpole/DRNE","owner":"tadpole","description":"The Implementation of \"Deep Recursive Network Embedding with Regular Equivalence\"(KDD 2018)","archived":false,"fork":false,"pushed_at":"2019-05-21T14:53:18.000Z","size":991,"stargazers_count":26,"open_issues_count":0,"forks_count":15,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-11-11T20:35:13.464Z","etag":null,"topics":["centrality","deep-neural-networks","network-embedding","network-representation-learning"],"latest_commit_sha":null,"homepage":"http://thumedialab.com/Deep-Recursive-Network-Embedding-with-Regular-Equivalence","language":"Python","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/tadpole.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}},"created_at":"2018-10-31T11:05:37.000Z","updated_at":"2023-03-23T07:22:53.000Z","dependencies_parsed_at":null,"dependency_job_id":"5aebff0e-6da9-4be0-99d3-582247f26847","html_url":"https://github.com/tadpole/DRNE","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/tadpole%2FDRNE","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tadpole%2FDRNE/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tadpole%2FDRNE/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tadpole%2FDRNE/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tadpole","download_url":"https://codeload.github.com/tadpole/DRNE/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251502537,"owners_count":21599591,"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":["centrality","deep-neural-networks","network-embedding","network-representation-learning"],"created_at":"2024-08-02T13:00:52.124Z","updated_at":"2025-04-29T12:34:38.377Z","avatar_url":"https://github.com/tadpole.png","language":"Python","funding_links":[],"categories":["Python","[Label Inference Methods](#content)","TensorFlow Implementations"],"sub_categories":["Graph Embedding Approaches"],"readme":"# DRNE\nThe Implementation of \"[Deep Recursive Network Embedding with Regular Equivalence](https://dl.acm.org/citation.cfm?doid=3219819.3220068)\"(KDD 2018).\n\n### Requirements\n```\nPython \u003e= 3.5.2\nscipy \u003e= 0.19.1\nnumpy \u003e= 1.13.1\ntensorflow == 1.2.0\nnetworkx \u003e= 1.11\n```\n\n### Usage\n##### Example Usage\n```\npython src/main.py --data_path dataset/barbell.edgelist --save_path result/barbell --save_suffix test \\\n      -s 16 -b 256 -lr 0.0025 --index_from_0 True\n```\n##### Full Command List\n```\nusage: Deep Recursive Network Embedding with Regular Equivalence\n       [-h] [--data_path DATA_PATH] [--save_path SAVE_PATH]\n       [--save_suffix SAVE_SUFFIX] [-s EMBEDDING_SIZE] [-e EPOCHS_TO_TRAIN]\n       [-b BATCH_SIZE] [-lr LEARNING_RATE] [--undirected UNDIRECTED]\n       [-a ALPHA] [-l LAMB] [-g GRAD_CLIP] [-K K]\n       [--sampling_size SAMPLING_SIZE] [--seed SEED]\n       [--index_from_0 INDEX_FROM_0]\n\noptional arguments:\n  -h, --help            show this help message and exit\n  --data_path DATA_PATH\n                        Directory to load data.\n  --save_path SAVE_PATH\n                        Directory to save data.\n  --save_suffix SAVE_SUFFIX\n                        Directory to save data.\n  -s EMBEDDING_SIZE, --embedding_size EMBEDDING_SIZE\n                        the embedding dimension size\n  -e EPOCHS_TO_TRAIN, --epochs_to_train EPOCHS_TO_TRAIN\n                        Number of epoch to train. Each epoch processes the\n                        training data once completely\n  -b BATCH_SIZE, --batch_size BATCH_SIZE\n                        Number of training examples processed per step\n  -lr LEARNING_RATE, --learning_rate LEARNING_RATE\n                        initial learning rate\n  --undirected UNDIRECTED\n                        whether it is an undirected graph\n  -a ALPHA, --alpha ALPHA\n                        the rate of structure loss and orth loss\n  -l LAMB, --lamb LAMB  the rate of structure loss and guilded loss\n  -g GRAD_CLIP, --grad_clip GRAD_CLIP\n                        clip gradients\n  -K K                  K-neighborhood\n  --sampling_size SAMPLING_SIZE\n                        sample number\n  --seed SEED           random seed\n  --index_from_0 INDEX_FROM_0\n                        whether the node index is from zero\n```\n### Cite\nIf you find this code useful, please cite our paper:\n```\n@inproceedings{tu2018deep,\n  title={Deep recursive network embedding with regular equivalence},\n  author={Tu, Ke and Cui, Peng and Wang, Xiao and Yu, Philip S and Zhu, Wenwu},\n  booktitle={Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery \\\u0026amp; Data Mining},\n  pages={2357--2366},\n  year={2018},\n  organization={ACM}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftadpole%2FDRNE","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftadpole%2FDRNE","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftadpole%2FDRNE/lists"}