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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 271–280 of 309 papers

TitleStatusHype
With Malice Towards None: Assessing Uncertainty via Equalized CoverageCode0
On the Role of Surrogates in Conformal Inference of Individual Causal EffectsCode0
On training locally adaptive CPCode0
HDI-Forest: Highest Density Interval Regression ForestCode0
Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regressionCode0
Conditional validity of heteroskedastic conformal regressionCode0
High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled ApproachCode0
Optimal Adaptive Prediction Intervals for Electricity Load Forecasting in Distribution Systems via Reinforcement LearningCode0
Conformal prediction for frequency-severity modelingCode0
Optimal Aggregation of Prediction Intervals under Unsupervised Domain ShiftCode0
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