{"id":21657039,"url":"https://github.com/tmthyln/armanets.jl","last_synced_at":"2025-07-30T07:43:01.049Z","repository":{"id":49018974,"uuid":"296169259","full_name":"tmthyln/ARMANets.jl","owner":"tmthyln","description":"An implementation of ARMA convolutional layers in Julia.","archived":false,"fork":false,"pushed_at":"2021-07-01T00:14:45.000Z","size":161,"stargazers_count":2,"open_issues_count":1,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-03-27T09:02:50.742Z","etag":null,"topics":["arma","convolutional-neural-networks","flux","julia","machine-learning"],"latest_commit_sha":null,"homepage":"https://tmthyln.github.io/ARMANets.jl/latest/","language":"Julia","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/tmthyln.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}},"created_at":"2020-09-16T23:27:33.000Z","updated_at":"2022-08-31T05:32:21.000Z","dependencies_parsed_at":"2022-08-27T22:53:47.569Z","dependency_job_id":null,"html_url":"https://github.com/tmthyln/ARMANets.jl","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tmthyln%2FARMANets.jl","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tmthyln%2FARMANets.jl/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tmthyln%2FARMANets.jl/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tmthyln%2FARMANets.jl/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tmthyln","download_url":"https://codeload.github.com/tmthyln/ARMANets.jl/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":244554120,"owners_count":20471173,"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":["arma","convolutional-neural-networks","flux","julia","machine-learning"],"created_at":"2024-11-25T09:19:09.586Z","updated_at":"2025-03-20T05:18:24.197Z","avatar_url":"https://github.com/tmthyln.png","language":"Julia","funding_links":[],"categories":[],"sub_categories":[],"readme":"# ARMANets.jl\nThis is an implementation of ARMA layers and ARMA networks in Julia, based on the paper [ARMA Nets: Expanding Receptive Field for Dense Prediction](https://arxiv.org/abs/2002.11609) (Su, Jiahao; Wang, Shiqi; Huang, Furong). The layers are a drop-in replacement (or addition) for standard convolutional layers.\n\nSee the [documentation](https://tmthyln.github.io/ARMANets.jl/latest/) for more details.\n\n## Citation\nThe original paper can be cited via\n```\n@misc{su2020arma,\n    title={ARMA Nets: Expanding Receptive Field for Dense Prediction},\n    author={Jiahao Su and Shiqi Wang and Furong Huang},\n    year={2020},\n    eprint={2002.11609},\n    archivePrefix={arXiv},\n    primaryClass={cs.CV}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftmthyln%2Farmanets.jl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftmthyln%2Farmanets.jl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftmthyln%2Farmanets.jl/lists"}