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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 21–30 of 309 papers

TitleStatusHype
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 Prediction with Upper and Lower Bound Models—0
Conformal forecasting for surgical instrument trajectory—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
Conformal Prediction for Electricity Price Forecasting in the Day-Ahead and Real-Time Balancing Market—0
Uncertainty Quantification of Wind Gust Predictions in the Northeast US: An Evidential Neural Network and Explainable Artificial Intelligence Approach—0
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