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Not all mistakes are equal
(The ACM Digital Library, 2020)
In many tasks, classifiers play a fundamental role in the way an agent behaves. Most rational agents collect sensor data from the environment, classify it, and act based on that classification. Recently, deep neural networks ...
Misclassification risk and uncertainty quantification in deep classifiers
(IEEE, 2021)
In this paper, we propose risk-calibrated evidential deep classifiers to reduce the costs associated with classification errors. We use two main approaches. The first is to develop methods to quantify the uncertainty of a ...
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