Evidential Deep Learning to Quantify Classification Uncertainty

NeurIPS 2018 Murat SensoyLance KaplanMelih Kandemir

Deterministic neural nets have been shown to learn effective predictors on a wide range of machine learning problems. However, as the standard approach is to train the network to minimize a prediction loss, the resultant model remains ignorant to its prediction confidence... (read more)

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