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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 151–200 of 309 papers

TitleStatusHype
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
Uncertainty-aware multi-fidelity surrogate modeling with noisy data—0
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
Asymptotically free sketched ridge ensembles: Risks, cross-validation, and tuningCode0
The WayHome: Long-term Motion Prediction on Dynamically Scaled—0
Distribution-free risk assessment of regression-based machine learning algorithms—0
Conformal Predictions for Longitudinal Data—0
Assessment of Prediction Intervals Using Uncertainty Characteristics Curves—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
Conditional validity of heteroskedastic conformal regressionCode0
Quantifying predictive uncertainty of aphasia severity in stroke patients with sparse heteroscedastic Bayesian high-dimensional 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
Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging—0
On training locally adaptive CPCode0
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
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
Lightweight, Uncertainty-Aware Conformalized Visual Odometry—0
Design-based conformal predictionCode0
Reliable Prediction Intervals with Directly Optimized Inductive Conformal Regression for Deep Learning—0
Will My Robot Achieve My Goals? Predicting the Probability that an MDP Policy Reaches a User-Specified Behavior Target—0
Conformal Quantitative Predictive Monitoring of STL Requirements for Stochastic ProcessesCode0
Confidence-Nets: A Step Towards better Prediction Intervals for regression Neural Networks on small datasets—0
Nonparametric Probabilistic Regression with Coarse Learners—0
Prediction intervals for economic fixed-event forecastsCode0
Nonparametric Quantile Regression: Non-Crossing Constraints and Conformal Prediction—0
Inference on Extreme Quantiles of Unobserved Individual HeterogeneityCode0
Uncertainty Quantification in Synthetic Controls with Staggered Treatment Adoption—0
Prediction intervals for neural network models using weighted asymmetric loss functions—0
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