CREDO: Epistemic-Aware Conformalized Credal Envelopes for Regression
arXiv 2603.06826•e67d6866a0ef4c434886324274ba02ae1845ccdbf19f5018951bb45ac7f8d745
ATE limitationsStein's methodanomaly detectioncausal inferencecausal maskingconformal predictioncredal methodsdifferential privacyepidemic forecastingepistemic uncertaintyfairness in MLfinancial time seriesgenerative modelsheavy-tailed distributionsleveling-downlikelihood quantile (LQ)minimax regretpolicy gradientpost-trainingprivacy-preserving MLprobabilistic forecastingrobust transfer learningsequence modelsspatiotemporal modelstruncated-mean estimation
Paper metadata
- arXiv ID
- 2603.06826
- Version
- Not specified by this published record
- Category
- Statistics — Machine Learning (stat.ML)
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Evidence and limitations
- Source ID
- arxiv_stat_ml
- Record identifier
- e67d6866a0ef4c434886324274ba02ae1845ccdbf19f5018951bb45ac7f8d745
- Enrichment time
- 2026-03-10T07:23:57Z
- AI-assisted enrichment
- Yes
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