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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 351–400 of 704 papers

TitleStatusHype
Formal Verification and Control with Conformal Prediction—0
PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification—0
Can Transformers Do Enumerative Geometry?Code0
RoCP-GNN: Robust Conformal Prediction for Graph Neural Networks in Node-Classification—0
Causally-Aware Spatio-Temporal Multi-Graph Convolution Network for Accurate and Reliable Traffic Prediction—0
Conformalized Interval Arithmetic with Symmetric CalibrationCode0
Adaptive Uncertainty Quantification for Generative AI—0
Conformalized Answer Set Prediction for Knowledge Graph Embedding—0
A conformalized learning of a prediction set with applications to medical imaging classification—0
Safety-Critical Control with Offline-Online Neural Network InferenceCode0
Robust Conformal Volume Estimation in 3D Medical ImagesCode0
Multi-group Uncertainty Quantification for Long-form Text Generation—0
Entropy Reweighted Conformal Classification—0
Conformal Predictions under Markovian Data—0
Conformal Thresholded Intervals for Efficient RegressionCode0
Conformal Performance Range Prediction for Segmentation Output Quality ControlCode0
Urban Traffic Forecasting with Integrated Travel Time and Data Availability in a Conformal Graph Neural Network Framework—0
Weighted Aggregation of Conformity Scores for Classification—0
Robust Yet Efficient Conformal Prediction SetsCode0
Conformal Inductive Graph Neural Networks—0
Meta-Analysis with Untrusted Data—0
Gaussian process interpolation with conformal prediction: methods and comparative analysis—0
Split Conformal Prediction under Data ContaminationCode0
TriQXNet: Forecasting Dst Index from Solar Wind Data Using an Interpretable Parallel Classical-Quantum Framework with Uncertainty Quantification—0
JANET: Joint Adaptive predictioN-region Estimation for Time-series—0
Trustworthy Classification through Rank-Based Conformal Prediction SetsCode0
Conformal Prediction for Causal Effects of Continuous TreatmentsCode0
Uncertainty-Aware Decarbonization for Datacenters—0
Improve ROI with Causal Learning and Conformal Prediction—0
Probabilistic Conformal Prediction with Approximate Conditional Validity—0
ConU: Conformal Uncertainty in Large Language Models with Correctness Coverage GuaranteesCode0
Length Optimization in Conformal PredictionCode0
Conformalized Link Prediction on Graph Neural Networks—0
Causal Responder Detection—0
Conformal time series decomposition with component-wise exchangeabilityCode0
Valid Error Bars for Neural Weather Models using Conformal Prediction—0
Debate as Optimization: Adaptive Conformal Prediction and Diverse Retrieval for Event Extraction—0
α-OCC: Uncertainty-Aware Camera-based 3D Semantic Occupancy Prediction—0
Evidential Uncertainty Sets in Deep Classifiers Using Conformal PredictionCode0
Learning Temporal Logic Predicates from Data with Statistical Guarantees—0
The Penalized Inverse Probability Measure for Conformal Classification—0
Conformalized Teleoperation: Confidently Mapping Human Inputs to High-Dimensional Robot Actions—0
Conformal Prediction for Class-wise Coverage via Augmented Label Rank CalibrationCode0
Robust Conformal Prediction Using Privileged InformationCode0
Normalizing Flows for Conformal RegressionCode0
Learning Cellular Network Connection Quality with Conformal—0
Certifiably Byzantine-Robust Federated Conformal PredictionCode0
Adapting Conformal Prediction to Distribution Shifts Without Labels—0
Single Trajectory Conformal Prediction—0
CONFINE: Conformal Prediction for Interpretable Neural Networks—0
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