{"id":22229761,"url":"https://github.com/graph-com/gssc","last_synced_at":"2025-07-20T02:08:02.267Z","repository":{"id":243904212,"uuid":"811924801","full_name":"Graph-COM/GSSC","owner":"Graph-COM","description":"[Preprint] Graph State Space Convolution (GSSC)","archived":false,"fork":false,"pushed_at":"2024-06-11T15:24:35.000Z","size":149,"stargazers_count":13,"open_issues_count":1,"forks_count":2,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-06-23T04:43:59.476Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","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/Graph-COM.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":"2024-06-07T15:16:43.000Z","updated_at":"2025-05-01T23:26:34.000Z","dependencies_parsed_at":"2024-06-12T00:39:19.136Z","dependency_job_id":"476a59be-6158-4a2d-ab24-152b2022f196","html_url":"https://github.com/Graph-COM/GSSC","commit_stats":null,"previous_names":["graph-com/gssc"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Graph-COM/GSSC","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Graph-COM%2FGSSC","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Graph-COM%2FGSSC/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Graph-COM%2FGSSC/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Graph-COM%2FGSSC/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Graph-COM","download_url":"https://codeload.github.com/Graph-COM/GSSC/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Graph-COM%2FGSSC/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":266057192,"owners_count":23870120,"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":"2024-12-03T01:12:15.217Z","updated_at":"2025-07-20T02:08:02.230Z","avatar_url":"https://github.com/Graph-COM.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003ch1 align=\"center\"\u003eGraph State Space Convolution (GSSC)\u003c/h1\u003e\n\u003cp align=\"center\"\u003e\n    \u003ca href=\"https://arxiv.org/abs/2406.05815\"\u003e\u003cimg src=\"https://img.shields.io/badge/-arXiv-grey?logo=gitbook\u0026logoColor=white\" alt=\"Paper\"\u003e\u003c/a\u003e\n    \u003ca href=\"https://github.com/Graph-COM/GSSC\"\u003e\u003cimg src=\"https://img.shields.io/badge/-Github-grey?logo=github\" alt=\"Github\"\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n\nThis repository contains the official implementation of GSSC as described in the paper: [What Can We Learn from State Space Models for Machine Learning on Graphs?](https://arxiv.org/abs/2406.05815) by Yinan Huang*, Siqi Miao*, and Pan Li.\n\n(*Equal contribution, listed in alphabetical order)\n\n## Installation\nAll required packages are listed in `environment.yml`.\n\n## Running the code\nReplace `--cfg` with the path to the configuration file and `--device` with the GPU device number like below:\n```\npython main.py --cfg configs/GSSC/peptides-func-GSSC.yaml --device 0 wandb.use False\n```\nThis command will train the model on the `peptides-func` dataset using the GSSC method with default hyperparameters.\n\n## Reproducing the results\nWe use wandb to log and sweep the results. To reproduce the reported results, one needs to create and login to a wandb account. Then, one can launch the sweep using the configuration files in the `configs` directory.\nFor example, to reproduce the tuned results of GSSC on the `peptides-func` dataset, one can launch the sweep using `configs/GSSC/peptides-func-GSSC-tune.yaml`.\n\n## Acknowledgement\nThis repository is built upon [GraphGPS (Rampasek et al., 2022)](https://github.com/rampasek/GraphGPS).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgraph-com%2Fgssc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgraph-com%2Fgssc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgraph-com%2Fgssc/lists"}