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Prediction Intervals

A prediction interval is an estimate of an interval in which a future observation will fall, with a certain probability, given what has already been observed. Prediction intervals are often used in regression analysis.

Papers

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Showing 121–130 of 309 papers

TitleStatusHype
Approaches for Uncertainty Quantification of AI-predicted Material Properties: A Comparison—0
Asymptotically free sketched ridge ensembles: Risks, cross-validation, and tuningCode0
The WayHome: Long-term Motion Prediction on Dynamically Scaled—0
Distribution-free risk assessment of regression-based machine learning algorithms—0
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves—0
Conformal Predictions for Longitudinal Data—0
Confidence Calibration for Systems with Cascaded Predictive Modules—0
Computation of Ultra-Short-Term Prediction Intervals of the Power Prosumption in Active Distribution Networks—0
Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regressionCode0
Conditional validity of heteroskedastic conformal regressionCode0
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