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Conformal Prediction

Conformal Prediction is a machine learning framework that provides valid measures of confidence for individual predictions. It offers a principled approach to quantify uncertainty in predictions without assuming any specific distribution for the data. This section features papers that explore various aspects of conformal prediction, including theoretical advancements, algorithmic developments, and applications across different domains.

Papers

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Showing 151–175 of 704 papers

TitleStatusHype
Extreme Conformal Prediction: Reliable Intervals for High-Impact Events—0
Robust Indoor Localization via Conformal Methods and Variational Bayesian Adaptive Filtering—0
Feature Fitted Online Conformal Prediction for Deep Time Series Forecasting ModelCode0
Reliably Bounding False Positives: A Zero-Shot Machine-Generated Text Detection Framework via Multiscaled Conformal Prediction—0
Fair Uncertainty Quantification for Depression Prediction—0
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach—0
Real-Time Privacy Preservation for Robot Visual Perception—0
Conformal Prediction with Corrupted Labels: Uncertain Imputation and Robust Re-weightingCode0
Conformal Prediction for Indoor Positioning with Correctness Coverage Guarantees—0
Uncertainty-aware Latent Safety Filters for Avoiding Out-of-Distribution Failures—0
Aerial Image Classification in Scarce and Unconstrained Environments via Conformal Prediction—0
Data-Driven Calibration of Prediction Sets in Large Vision-Language Models Based on Inductive Conformal Prediction—0
Statistical Guarantees in Synthetic Data through Conformal Adversarial Generation—0
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
Learning Enhanced Structural Representations with Block-Based Uncertainties for Ocean Floor MappingCode0
SConU: Selective Conformal Uncertainty in Large Language Models—0
Safety Monitoring for Learning-Enabled Cyber-Physical Systems in Out-of-Distribution Scenarios—0
Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer—0
Leave-One-Out Stable Conformal PredictionCode0
Conditional Conformal Risk Adaptation—0
FAIR-SIGHT: Fairness Assurance in Image Recognition via Simultaneous Conformal Thresholding and Dynamic Output Repair—0
Conformalized Generative Bayesian Imaging: An Uncertainty Quantification Framework for Computational Imaging—0
Assumption-free fidelity bounds for hardware noise characterization—0
Conformal Robust Beamforming via Generative Channel Models—0
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