110 citations · 186 across the 9 of their papers we have counts for
3 papers · 1 filter
Bayesian Confidence Calibration for Epistemic Uncertainty Modelling
Fabian Küppers, Jan Kronenberger, Jonas Schneider +1
Modern neural networks have found to be miscalibrated in terms of confidence calibration, i.e., their predicted confidence scores do not reflect the observed accuracy or precision.…
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety
Sebastian Houben, Stephanie Abrecht, Maram Akila +38
The use of deep neural networks (DNNs) in safety-critical applications like mobile health and autonomous driving is challenging due to numerous model-inherent shortcomings. These s…
From Black-box to White-box: Examining Confidence Calibration under different Conditions
Franziska Schwaiger, Maximilian Henne, Fabian Küppers +3
Confidence calibration is a major concern when applying artificial neural networks in safety-critical applications. Since most research in this area has focused on classification i…