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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 1–10 of 309 papers

TitleStatusHype
Foundation models for time series forecasting: Application in conformal prediction—0
A Wireless Foundation Model for Multi-Task Prediction—0
On the relationship between prediction intervals, tests of sharp nulls and inference on realized treatment effects in settings with few treated units—0
LLM-Powered CPI Prediction Inference with Online Text Time SeriesCode0
Diffusion-based Time Series Forecasting for Sewerage Systems—0
Individualised Counterfactual Examples Using Conformal Prediction Intervals—0
Deep Learning-Based BMD Estimation from Radiographs with Conformal Uncertainty Quantification—0
STACI: Spatio-Temporal Aleatoric Conformal Inference—0
MetaSTNet: Multimodal Meta-learning for Cellular Traffic Conformal Prediction—0
Unveil Sources of Uncertainty: Feature Contribution to Conformal Prediction Intervals—0
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