-
Parameterized Temperature Scaling for Boosting the Expressive Power in Post-Hoc Uncertainty Calibration
We address the problem of uncertainty calibration and introduce a novel ...
02/24/2021 ∙ by Christian Tomani, et al. ∙
0
∙
share
read it
-
Post-hoc Uncertainty Calibration for Domain Drift Scenarios
We address the problem of uncertainty calibration. While standard deep n...
12/20/2020 ∙ by Christian Tomani, et al. ∙
0
∙
share
read it
-
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration
To facilitate a wide-spread acceptance of AI systems guiding decision ma...
12/20/2020 ∙ by Christian Tomani, et al. ∙
0
∙
share
read it
