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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 151–200 of 704 papers

TitleStatusHype
Conformal Prediction and MLLM aided Uncertainty Quantification in Scene Graph Generation—0
CHAMP: Conformalized 3D Human Multi-Hypothesis Pose Estimators—0
Conformal Prediction with Cellwise Outliers: A Detect-then-Impute Approach—0
A Conformal Prediction Approach to Explore Functional Data—0
Early-Exit Neural Networks with Nested Prediction Sets—0
Conformal Predictions for Longitudinal Data—0
Conformal Prediction Sets for Deep Generative Models via Reduction to Conformal Regression—0
Conformal Off-Policy Prediction in Contextual Bandits—0
Adaptive Uncertainty Quantification for Generative AI—0
Conformal Prediction Sets with Improved Conditional Coverage using Trust Scores—0
Conformal Predictions under Markovian Data—0
Adaptive Temperature Scaling with Conformal Prediction—0
Causally-Aware Spatio-Temporal Multi-Graph Convolution Network for Accurate and Reliable Traffic Prediction—0
A conformalized learning of a prediction set with applications to medical imaging classification—0
Conformal Nucleus Sampling—0
Conformal Mixed-Integer Constraint Learning with Feasibility Guarantees—0
CAP: A General Algorithm for Online Selective Conformal Prediction with FCR Control—0
Conformal Methods for Quantifying Uncertainty in Spatiotemporal Data: A Survey—0
Conformal Meta-learners for Predictive Inference of Individual Treatment Effects—0
Anomalous Edge Detection in Edge Exchangeable Social Network Models—0
Conformal Object Detection by Sequential Risk Control—0
Conformal Off-Policy Evaluation in Markov Decision Processes—0
Causal Responder Detection—0
Conformal Off-Policy Prediction for Multi-Agent Systems—0
Conformal Prediction on Quantifying Uncertainty of Dynamic Systems—0
Cautious Deep Learning—0
Any2Any: Incomplete Multimodal Retrieval with Conformal Prediction—0
Conformal Loss-Controlling Prediction—0
Adaptive Conformal Regression with Jackknife+ Rescaled Scores—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 k-NN Anomaly Detector for Univariate Data Streams—0
Conformal Prediction as Bayesian Quadrature—0
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems—0
Conformal Prediction Bands for Two-Dimensional Functional Time Series—0
An Investigation on Machine Learning Predictive Accuracy Improvement and Uncertainty Reduction using VAE-based Data Augmentation—0
Model-Free Kernel Conformal Depth Measures Algorithm for Uncertainty Quantification in Regression Models in Separable Hilbert Spaces—0
Closing the Loop on Runtime Monitors with Fallback-Safe MPC—0
Conformalizing Machine Translation Evaluation—0
Conformalized Unconditional Quantile Regression—0
Conformal Prediction for Distribution-free Optimal Control of Linear Stochastic Systems—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
Applying Regression Conformal Prediction with Nearest Neighbors to time series data—0
Conformal Prediction for Hierarchical Data—0
Collaborative Multi-Object Tracking with Conformal Uncertainty Propagation—0
Conformalized Teleoperation: Confidently Mapping Human Inputs to High-Dimensional Robot Actions—0
Online Calibrated and Conformal Prediction Improves Bayesian Optimization—0
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