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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 426–450 of 704 papers

TitleStatusHype
Prediction and outlier detection in classification problems—0
Conformalised Conditional Normalising Flows for Joint Prediction Regions in time series—0
Model-free generalized fiducial inference—0
Unveiling Nonlinear Dynamics in Catastrophe Bond Pricing: A Machine Learning Perspective—0
Aggregating Predictions on Multiple Non-disclosed Datasets using Conformal Prediction—0
Probabilistically robust conformal prediction—0
Provably Reliable Conformal Prediction Sets in the Presence of Data Poisoning—0
Agreeing to Stop: Reliable Latency-Adaptive Decision Making via Ensembles of Spiking Neural Networks—0
Quantifying Deep Learning Model Uncertainty in Conformal Prediction—0
Conformalized Answer Set Prediction for Knowledge Graph Embedding—0
Raman Spectrum Matching with Contrastive Representation Learning—0
Randomness, exchangeability, and conformal prediction—0
Reachability Barrier Networks: Learning Hamilton-Jacobi Solutions for Smooth and Flexible Control Barrier Functions—0
Real-time Out-of-distribution Detection in Learning-Enabled Cyber-Physical Systems—0
Real-Time Privacy Preservation for Robot Visual Perception—0
Rectifying Conformity Scores for Better Conditional Coverage—0
Recursively Feasible Shrinking-Horizon MPC in Dynamic Environments with Conformal Prediction Guarantees—0
Redefining Machine Unlearning: A Conformal Prediction-Motivated Approach—0
Conformalized Credal Regions for Classification with Ambiguous Ground Truth—0
Regression Conformal Prediction with Nearest Neighbours—0
Relational Conformal Prediction for Correlated Time Series—0
Conformalized Decision Risk Assessment—0
Reliable Prediction Errors for Deep Neural Networks Using Test-Time Dropout—0
Reliable Prediction Intervals with Regression Neural Networks—0
Conformalized-DeepONet: A Distribution-Free Framework for Uncertainty Quantification in Deep Operator Networks—0
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