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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 41–50 of 309 papers

TitleStatusHype
An Interpretable Probabilistic Model for Short-Term Solar Power Forecasting Using Natural Gradient BoostingCode1
Deep Kernel Survival Analysis and Subject-Specific Survival Time Prediction IntervalsCode1
Conffusion: Confidence Intervals for Diffusion ModelsCode1
Dual Accuracy-Quality-Driven Neural Network for Prediction Interval GenerationCode1
Forecasting CPI inflation under economic policy and geopolitical uncertaintiesCode1
CatBoostLSS -- An extension of CatBoost to probabilistic forecastingCode1
A Data-Driven Supervised Machine Learning Approach to Estimating Global Ambient Air Pollution Concentrations With Associated Prediction IntervalsCode1
CODiT: Conformal Out-of-Distribution Detection in Time-Series DataCode1
Locally Valid and Discriminative Prediction Intervals for Deep Learning ModelsCode1
Uncertainty Characteristics Curves: A Systematic Assessment of Prediction IntervalsCode1
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