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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 161–170 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
Conformal Predictions for Longitudinal Data—0
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves—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
Conditional validity of heteroskedastic conformal regressionCode0
Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regressionCode0
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