{"payload":{"header_redesign_enabled":false,"results":[{"id":"784596896","archived":false,"color":"#3572A5","followers":6,"has_funding_file":false,"hl_name":"idiap/inference-from-real-world-sparse-measurements","hl_trunc_description":"Implementation of the Multi-Layer Self-Attention, a state-of-the-art model designed for wind nowcasting tasks","language":"Python","mirror":false,"owned_by_organization":true,"public":true,"repo":{"repository":{"id":784596896,"name":"inference-from-real-world-sparse-measurements","owner_id":1338804,"owner_login":"idiap","updated_at":"2024-04-10T11:38:21.336Z","has_issues":true}},"sponsorable":false,"topics":[],"type":"Public","help_wanted_issues_count":0,"good_first_issue_issues_count":0,"starred_by_current_user":false}],"type":"repositories","page":1,"page_count":1,"elapsed_millis":81,"errors":[],"result_count":1,"facets":[],"protected_org_logins":[],"topics":null,"query_id":"","logged_in":false,"sign_up_path":"/signup?source=code_search_results","sign_in_path":"/login?return_to=https%3A%2F%2Fgithub.com%2Fsearch%3Fq%3Drepo%253Aidiap%252Finference-from-real-world-sparse-measurements%2B%2Blanguage%253APython","metadata":null,"csrf_tokens":{"/idiap/inference-from-real-world-sparse-measurements/star":{"post":"Vd_8AOK-V9lhLLb9c1moLZRJEIq6H2IAmiXobNKMEeFJW5goZy3SquKnCEdhhN8CJW6-0zGaC6M6RPIuwAXRGA"},"/idiap/inference-from-real-world-sparse-measurements/unstar":{"post":"mGf_lvgx8a3kCN_ZBJmiAhrkaDMXIekNzp2m2hAwsOlwtyJyjZ7x4Rtw4hZoNqVk3Z_FBGYRPZd6gkDr4VMLOQ"},"/sponsors/batch_deferred_sponsor_buttons":{"post":"YPFtRZRFZJmB556_ZDNz8zDOzE72Duto7tRgH8j8rdMyTuOov17w001RRVMg4Jrd1N_kssRdmZAi1yQQ4aho7Q"}}},"title":"Repository search results"}