[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-84643":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":12,"openIssues":14,"contributorsCount":14,"subscribersCount":14,"size":14,"stars1d":14,"stars7d":14,"stars30d":14,"stars90d":14,"forks30d":14,"starsTrendScore":14,"compositeScore":15,"rankGlobal":10,"rankLanguage":10,"license":16,"archived":17,"fork":17,"defaultBranch":18,"hasWiki":17,"hasPages":17,"topics":19,"createdAt":10,"pushedAt":10,"updatedAt":20,"readmeContent":10,"aiSummary":10,"trendingCount":14,"starSnapshotCount":14,"syncStatus":13,"lastSyncTime":21,"discoverSource":22},84643,"HEPA","Forgis-Labs\u002FHEPA","Forgis-Labs","HEPA: Self-supervised horizon-conditioned event predictive architecture for time series. Spotlight at FMSD @ ICML 2026.","https:\u002F\u002Fwww.forgis.com\u002Fpapers\u002Fhepa.html",null,"Python",51,2,0,37.43,"Other",false,"main",[],"2026-06-13 04:01:39","2026-06-13 02:30:12","CREATED_QUERY"]