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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 176–200 of 704 papers

TitleStatusHype
Implementing Trust in Non-Small Cell Lung Cancer Diagnosis with a Conformalized Uncertainty-Aware AI Framework in Whole-Slide ImagesCode0
Uncertainty quantification for improving radiomic-based models in radiation pneumonitis prediction—0
Adaptive Conformal Inference by Betting—0
Neural Conformal Control for Time Series ForecastingCode1
Distribution-Free Uncertainty Quantification in Mechanical Ventilation Treatment: A Conformal Deep Q-Learning Framework—0
A Conformal Approach to Feature-based Newsvendor under Model Misspecification—0
On the Role of Surrogates in Conformal Inference of Individual Causal EffectsCode0
Conformal Prediction on Quantifying Uncertainty of Dynamic Systems—0
Distribution free uncertainty quantification in neuroscience-inspired deep operators—0
Disturbance-Adaptive Data-Driven Predictive Control: Trading Comfort Violations for Savings in Building Climate Control—0
CUPS: Improving Human Pose-Shape Estimators with Conformalized Deep Uncertainty—0
Fundus Image-based Visual Acuity Assessment with PAC-GuaranteesCode0
Tube Loss: A Novel Approach for Prediction Interval Estimation and probabilistic forecastingCode0
Are foundation models for computer vision good conformal predictors?—0
GeoConformal prediction: a model-agnostic framework of measuring the uncertainty of spatial prediction—0
An In-Depth Examination of Risk Assessment in Multi-Class Classification Algorithms—0
Safe Adaptive Cruise Control Under Perception Uncertainty: A Deep Ensemble and Conformal Tube Model Predictive Control Approach—0
Spatial Conformal Inference through Localized Quantile Regression—0
Predictive Inference With Fast Feature Conformal PredictionCode0
Enhancing the conformal predictability of context-aware recommendation systems by using Deep Autoencoders—0
Conformal Prediction for Distribution-free Optimal Control of Linear Stochastic Systems—0
Distribution-Free Calibration of Statistical Confidence SetsCode0
Spatio-Temporal Conformal Prediction for Power Outage Data—0
Confidence-Aware Deep Learning for Load Plan Adjustments in the Parcel Service Industry—0
Robust Bayesian Optimization via Localized Online Conformal PredictionCode0
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