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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 651–675 of 704 papers

TitleStatusHype
Conformalized Survival AnalysisCode0
Distribution-free uncertainty quantification for classification under label shift—0
Retrain or not retrain: Conformal test martingales for change-point detection—0
Few-shot Conformal Prediction with Auxiliary TasksCode0
Boost AI Power: Data Augmentation Strategies with unlabelled Data and Conformal Prediction, a Case in Alternative Herbal Medicine Discrimination with Electronic Nose—0
Copula-based conformal prediction for Multi-Target Regression—0
Online Multivalid Learning: Means, Moments, and Prediction Intervals—0
Testing for concept shift online—0
Improving Fairness in Criminal Justice Algorithmic Risk Assessments Using Conformal Prediction Sets—0
Conformal Rule-Based Multi-label Classification—0
Making learning more transparent using conformalized performance prediction—0
Less is More: Rejecting Unreliable Reviews for Product Question AnsweringCode0
Conformal Prediction Intervals for Neural Networks Using Cross Validation—0
AutoCP: Automated Pipelines for Accurate Prediction Intervals—0
Learning Robust Decision Policies from Observational Data—0
Conformal Prediction: a Unified Review of Theory and New ChallengesCode0
Training conformal predictors—0
Exchangeability, Conformal Prediction, and Rank Tests—0
Knowing what you know: valid and validated confidence sets in multiclass and multilabel prediction—0
Detecting Adversarial Examples in Learning-Enabled Cyber-Physical Systems using Variational Autoencoder for Regression—0
Trusted Confidence Bounds for Learning Enabled Cyber-Physical Systems—0
Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems—0
Validity, consonant plausibility measures, and conformal prediction—0
Conformal e-prediction—0
Assurance Monitoring of Cyber-Physical Systems with Machine Learning Components—0
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