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3 papers
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.…
Dependency Decomposition and a Reject Option for Explainable Models
Jan Kronenberger, Anselm Haselhoff
Deploying machine learning models in safety-related do-mains (e.g. autonomous driving, medical diagnosis) demands for approaches that are explainable, robust against adversarial at…
Multivariate Confidence Calibration for Object Detection
Fabian Küppers, Jan Kronenberger, Amirhossein Shantia +1
Unbiased confidence estimates of neural networks are crucial especially for safety-critical applications. Many methods have been developed to calibrate biased confidence estimates.…