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cs.LG2019
Epistemic Uncertainty Quantification in Deep Learning Classification by the Delta Method
Geir K. Nilsen, Antonella Z. Munthe-Kaas, Hans J. Skaug +1
The Delta method is a classical procedure for quantifying epistemic uncertainty in statistical models, but its direct application to deep neural networks is prevented by the large…
cs.LG2019★ 7 cited
Efficient Computation of Hessian Matrices in TensorFlow
Geir K. Nilsen, Antonella Z. Munthe-Kaas, Hans J. Skaug +1
The Hessian matrix has a number of important applications in a variety of different fields, such as optimzation, image processing and statistics. In this paper we focus on the prac…