10 citations · 17 across the 7 of their papers we have counts for
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cs.LG2020
Post-hoc Uncertainty Calibration for Domain Drift Scenarios
Christian Tomani, Sebastian Gruber, Muhammed Ebrar Erdem +2
We address the problem of uncertainty calibration. While standard deep neural networks typically yield uncalibrated predictions, calibrated confidence scores that are representativ…
cs.LG2020★ 3 cited
Towards Trustworthy Predictions from Deep Neural Networks with Fast Adversarial Calibration
Christian Tomani, Florian Buettner
To facilitate a wide-spread acceptance of AI systems guiding decision making in real-world applications, trustworthiness of deployed models is key. That is, it is crucial for predi…