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Found 5 papers, 4 papers with code
Conformal time series decomposition with component-wise exchangeability
We find that the method provides promising results on well-structured time series, but can be limited by factors such as the decomposition step for more complex data.
Fast yet Safe: Early-Exiting with Risk Control
Scaling machine learning models significantly improves their performance.
Adaptive Bounding Box Uncertainties via Two-Step Conformal Prediction
Thus, we develop a novel two-step conformal approach that propagates uncertainty in predicted class labels into the uncertainty intervals of bounding boxes.
A powerful rank-based correction to multiple testing under positive dependency
We develop a novel multiple hypothesis testing correction with family-wise error rate (FWER) control that efficiently exploits positive dependencies between potentially correlated statistical hypothesis tests.
Uncertainty Quantification for Image-based Traffic Prediction across Cities
We compare two epistemic and two aleatoric UQ methods on both temporal and spatio-temporal transfer tasks, and find that meaningful uncertainty estimates can be recovered.
