{"id":13481085,"url":"https://github.com/alge24/eigenpooling","last_synced_at":"2025-03-27T11:31:46.451Z","repository":{"id":218341186,"uuid":"225071611","full_name":"alge24/eigenpooling","owner":"alge24","description":"An implementation of KDD paper \"Graph Convolutional Networks with EigenPooling\" ","archived":false,"fork":false,"pushed_at":"2019-12-02T04:37:37.000Z","size":3658,"stargazers_count":47,"open_issues_count":3,"forks_count":15,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-10-30T14:43:28.372Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/alge24.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,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-11-30T21:24:55.000Z","updated_at":"2024-09-27T00:00:14.000Z","dependencies_parsed_at":null,"dependency_job_id":"d3a1ace5-8a97-4fea-beb7-c5e12061f5e1","html_url":"https://github.com/alge24/eigenpooling","commit_stats":null,"previous_names":["alge24/eigenpooling"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alge24%2Feigenpooling","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alge24%2Feigenpooling/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alge24%2Feigenpooling/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alge24%2Feigenpooling/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alge24","download_url":"https://codeload.github.com/alge24/eigenpooling/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245836209,"owners_count":20680335,"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":[],"created_at":"2024-07-31T17:00:48.538Z","updated_at":"2025-03-27T11:31:46.446Z","avatar_url":"https://github.com/alge24.png","language":"Python","funding_links":[],"categories":["Deep Learning"],"sub_categories":[],"readme":"# Graph Convolutional Networks with EigenPooling \nPytorch implementation of [eigenpooling](https://arxiv.org/pdf/1904.13107.pdf). Some parts of the code are adapdted from the implementation of [diffpool](https://github.com/RexYing/diffpool).\n\nFor more details of the algorithm, please refer to our [paper](https://arxiv.org/pdf/1904.13107.pdf). If you find this work useful and use it in your research, please cite our paper.\n\n```\n@inproceedings{Ma:2019:GCN:3292500.3330982,\n author = {Ma, Yao and Wang, Suhang and Aggarwal, Charu C. and Tang, Jiliang},\n title = {Graph Convolutional Networks with EigenPooling},\n booktitle = {Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \\\u0026 Data Mining},\n series = {KDD '19},\n year = {2019},\n isbn = {978-1-4503-6201-6},\n location = {Anchorage, AK, USA},\n pages = {723--731},\n numpages = {9},\n url = {http://doi.acm.org/10.1145/3292500.3330982},\n doi = {10.1145/3292500.3330982},\n acmid = {3330982},\n publisher = {ACM},\n address = {New York, NY, USA},\n keywords = {graph classification, graph convolution networks, pooling, spectral graph theory},\n} \n\n```\n\n#### Usage\nPlease check run_example.sh for an example of running the code.\n\n#### Preprocessed datasets\nYou may download the preprocessed datasets [here](https://drive.google.com/open?id=1-8FrJxWFczCAnhOWVi9fq0SdwpA7pM_p) to save the time of preprocessing data.\n\n#### Known Issue\nRunning on GPU may result in sub-optimal performance on some of the datasets inclduing ENZYMES, NCI1 and NCI109.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falge24%2Feigenpooling","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falge24%2Feigenpooling","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falge24%2Feigenpooling/lists"}