204 citations · 213 across the 25 of their papers we have counts for
4 papers · 1 filter
Consistent and Asymptotically Unbiased Estimation of Proper Calibration Errors
Teodora Popordanoska, Sebastian G. Gruber, Aleksei Tiulpin +2
Proper scoring rules evaluate the quality of probabilistic predictions, playing an essential role in the pursuit of accurate and well-calibrated models. Every proper score decompos…
Estimating calibration error under label shift without labels
Teodora Popordanoska, Gorjan Radevski, Tinne Tuytelaars +1
In the face of dataset shift, model calibration plays a pivotal role in ensuring the reliability of machine learning systems. Calibration error (CE) is an indicator of the alignmen…
Beyond Classification: Definition and Density-based Estimation of Calibration in Object Detection
Teodora Popordanoska, Aleksei Tiulpin, Matthew B. Blaschko
Despite their impressive predictive performance in various computer vision tasks, deep neural networks (DNNs) tend to make overly confident predictions, which hinders their widespr…
Understanding metric-related pitfalls in image analysis validation
Annika Reinke, Minu D. Tizabi, Michael Baumgartner +75
Validation metrics are key for the reliable tracking of scientific progress and for bridging the current chasm between artificial intelligence (AI) research and its translation int…