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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 601–625 of 704 papers

TitleStatusHype
Uncertainty Quantification for Collaborative Object Detection Under Adversarial Attacks—0
Conformal Off-Policy Prediction for Multi-Agent Systems—0
Conformal Off-Policy Prediction in Contextual Bandits—0
Confident Object Detection via Conformal Prediction and Conformal Risk Control: an Application to Railway Signaling—0
Robust Deep Reinforcement Learning for Volt-VAR Optimization in Active Distribution System under Uncertainty—0
Robust Flow-based Conformal Inference (FCI) with Statistical Guarantee—0
Confidence Calibration for Systems with Cascaded Predictive Modules—0
Conformal Policy Learning for Sensorimotor Control Under Distribution Shifts—0
Conformal Prediction: A Data Perspective—0
Conformal Prediction and Human Decision Making—0
Conformal Prediction and MLLM aided Uncertainty Quantification in Scene Graph Generation—0
Conformal Prediction as Bayesian Quadrature—0
Robust Indoor Localization via Conformal Methods and Variational Bayesian Adaptive Filtering—0
Conformal Prediction Bands for Two-Dimensional Functional Time Series—0
Conformal Prediction based Spectral Clustering—0
Robust Online Conformal Prediction under Uniform Label Noise—0
Adversarially Robust Conformal Prediction—0
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction—0
Conformal Prediction for Distribution-free Optimal Control of Linear Stochastic Systems—0
Uncertainty quantification for improving radiomic-based models in radiation pneumonitis prediction—0
Conformal Prediction for Electricity Price Forecasting in the Day-Ahead and Real-Time Balancing Market—0
Conformal Prediction for Federated Uncertainty Quantification Under Label Shift—0
Conformal Prediction for Federated Graph Neural Networks with Missing Neighbor Information—0
Uncertainty Quantification for Neurosymbolic Programs via Compositional Conformal Prediction—0
Conformal Prediction for Hierarchical Data—0
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