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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 101–150 of 309 papers

TitleStatusHype
Conformal prediction for multi-dimensional time series by ellipsoidal setsCode1
Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecasting—0
Failures and Successes of Cross-Validation for Early-Stopped Gradient Descent—0
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks—0
Efficient Normalized Conformal Prediction and Uncertainty Quantification for Anti-Cancer Drug Sensitivity Prediction with Deep Regression Forests—0
A Data-Driven Supervised Machine Learning Approach to Estimating Global Ambient Air Pollution Concentrations With Associated Prediction IntervalsCode1
Regression Trees for Fast and Adaptive Prediction IntervalsCode1
Self-Calibrating Conformal PredictionCode1
Bellman Conformal Inference: Calibrating Prediction Intervals For Time SeriesCode1
Conformal Convolution and Monte Carlo Meta-learners for Predictive Inference of Individual Treatment EffectsCode1
Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage GuaranteesCode1
Uncertainty-aware multi-fidelity surrogate modeling with noisy data—0
Forecasting CPI inflation under economic policy and geopolitical uncertaintiesCode1
Reliable Prediction Intervals with Regression Neural Networks—0
Sequential inductive prediction intervals—0
Adaptability of Computer Vision at the Tactical Edge: Addressing Environmental Uncertainty—0
Conformalized Deep Splines for Optimal and Efficient Prediction SetsCode0
Stability of Random Forests and Coverage of Random-Forest Prediction Intervals—0
Guaranteed Coverage Prediction Intervals with Gaussian Process Regression—0
UncertaintyPlayground: A Fast and Simplified Python Library for Uncertainty EstimationCode0
Approaches for Uncertainty Quantification of AI-predicted Material Properties: A Comparison—0
The WayHome: Long-term Motion Prediction on Dynamically Scaled—0
Asymptotically free sketched ridge ensembles: Risks, cross-validation, and tuningCode0
Distribution-free risk assessment of regression-based machine learning algorithms—0
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves—0
Conformal Predictions for Longitudinal Data—0
Confidence Calibration for Systems with Cascaded Predictive Modules—0
Computation of Ultra-Short-Term Prediction Intervals of the Power Prosumption in Active Distribution Networks—0
Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional regressionCode0
Conditional validity of heteroskedastic conformal regressionCode0
Beta quantile regression for robust estimation of uncertainty in the presence of outliers—0
An LSTM-Based Predictive Monitoring Method for Data with Time-varying Variability—0
Conformal prediction for frequency-severity modelingCode0
Uncertainty Quantification of the Virial Black Hole Mass with Conformal PredictionCode0
UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation—0
Wasserstein Generative Regression—0
Ensembled Prediction Intervals for Causal Outcomes Under Hidden Confounding—0
Integrating Uncertainty Awareness into Conformalized Quantile RegressionCode0
On training locally adaptive CPCode0
Conformal Prediction with Missing ValuesCode1
Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging—0
Evaluating Machine Translation Quality with Conformal Predictive Distributions—0
Adaptive Conformal Regression with Jackknife+ Rescaled Scores—0
Perturbation-Assisted Sample Synthesis: A Novel Approach for Uncertainty QuantificationCode0
Using neural ordinary differential equations to predict complex ecological dynamics from population density data—0
Uncertainty Aware Neural Network from Similarity and SensitivityCode1
Quantile Extreme Gradient Boosting for Uncertainty Quantification—0
Conformal Regression in Calorie Prediction for Team Jumbo-Visma—0
Development and Evaluation of Conformal Prediction Methods for QSAR—0
Extrapolation to complete basis-set limit in density-functional theory by quantile random-forest models—0
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