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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 51–100 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
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
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
Data-Driven vs Traditional Approaches to Power Transformer's Top-Oil Temperature Estimation—0
Conformal Inference of Individual Treatment Effects Using Conditional Density Estimates—0
Prediction Interval Construction Method for Electricity Prices—0
Uncertainty-Aware Online Extrinsic Calibration: A Conformal Prediction Approach—0
Uncertainty Estimation for Path Loss and Radio Metric ModelsCode0
On the Role of Surrogates in Conformal Inference of Individual Causal EffectsCode0
Fundus Image-based Visual Acuity Assessment with PAC-GuaranteesCode0
Multi-Scale Kinetics Modeling for Cell Culture Process with Metabolic State Transition—0
Spatial Conformal Inference through Localized Quantile Regression—0
Context-Based Echo State Networks with Prediction Confidence for Human-Robot Shared Control—0
Density-Calibrated Conformal Quantile Regression—0
Uncertainty measurement for complex event prediction in safety-critical systems—0
Conformal Prediction for Multimodal RegressionCode0
Target Strangeness: A Novel Conformal Prediction Difficulty EstimatorCode0
Building Conformal Prediction Intervals with Approximate Message PassingCode0
DST-TransitNet: A Dynamic Spatio-Temporal Deep Learning Model for Scalable and Efficient Network-Wide Prediction of Station-Level Transit Ridership—0
Conformal Predictive Portfolio Selection—0
Bin-Conditional Conformal Prediction of Fatalities from Armed Conflict—0
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