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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 71–80 of 309 papers

TitleStatusHype
Online Selective Conformal Prediction: Errors and Solutions—0
NeuroSep-CP-LCB: A Deep Learning-based Contextual Multi-armed Bandit Algorithm with Uncertainty Quantification for Early Sepsis PredictionCode0
Probabilistic Neural Networks (PNNs) with t-Distributed Outputs: Adaptive Prediction Intervals Beyond Gaussian Assumptions—0
Probabilistic Reasoning with LLMs for k-anonymity Estimation—0
Segmentation-Guided CT Synthesis with Pixel-Wise Conformal Uncertainty Bounds—0
Conformal forecasting for surgical instrument trajectory—0
Conformal Prediction with Upper and Lower Bound Models—0
Joint Registration and Conformal Prediction for Partially Observed Functional Data—0
Conformal Prediction under Levy-Prokhorov Distribution Shifts: Robustness to Local and Global PerturbationsCode0
Generalized Venn and Venn-Abers Calibration with Applications in Conformal Prediction—0
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