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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 51–75 of 309 papers

TitleStatusHype
Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval PredictorsCode1
XGBoostLSS -- An extension of XGBoost to probabilistic forecastingCode1
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
Extreme Conformal Prediction: Reliable Intervals for High-Impact Events—0
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach—0
A Minimax-MDP Framework with Future-imposed Conditions for Learning-augmented Problems—0
Model uncertainty quantification using feature confidence sets for outcome excursionsCode0
From predictions to confidence intervals: an empirical study of conformal prediction methods for in-context learning—0
Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning—0
Adapting GT2-FLS for Uncertainty Quantification: A Blueprint Calibration StrategyCode0
ConfEviSurrogate: A Conformalized Evidential Surrogate Model for Uncertainty Quantification—0
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
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