Quantifying Classification Uncertainty using Regularized Evidential Neural Networks

15 Oct 2019Xujiang ZhaoYuzhe OuLance KaplanFeng ChenJin-Hee Cho

Traditional deep neural nets (NNs) have shown the state-of-the-art performance in the task of classification in various applications. However, NNs have not considered any types of uncertainty associated with the class probabilities to minimize risk due to misclassification under uncertainty in real life... (read more)

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