3 papers
cs.LG2021
A Comparison of the Delta Method and the Bootstrap in Deep Learning Classification
Geir K. Nilsen, Antonella Z. Munthe-Kaas, Hans J. Skaug +1
We validate the recently introduced deep learning classification adapted Delta method by a comparison with the classical Bootstrap. We show that there is a strong linear relationsh…
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
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…