1 citations · 5 across the 13 of their papers we have counts for
3 papers · 1 filter
Conformal time series decomposition with component-wise exchangeability
Derck W. E. Prinzhorn, Thijmen Nijdam, Putri A. van der Linden +1
Conformal prediction offers a practical framework for distribution-free uncertainty quantification, providing finite-sample coverage guarantees under relatively mild assumptions on…
Fast yet Safe: Early-Exiting with Risk Control
Metod Jazbec, Alexander Timans, Tin Hadži Veljković +4
Scaling machine learning models significantly improves their performance. However, such gains come at the cost of inference being slow and resource-intensive. Early-exit neural net…
Adaptive Bounding Box Uncertainties via Two-Step Conformal Prediction
Alexander Timans, Christoph-Nikolas Straehle, Kaspar Sakmann +1
Quantifying a model's predictive uncertainty is essential for safety-critical applications such as autonomous driving. We consider quantifying such uncertainty for multi-object det…