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Model-Agnostic Online Certificate-Driven Calibration for Time Series Forecasting Under Distribution Shift
Time series out-of-distribution generalization requires forecasters to remain reliable when deployment dynamics differ from training conditions due to covariate shift, concept shift, and temporal dependence. Probably Approximately Correct Bayesian domain adaptation provides computable certificates b
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