2021
Improving predictions of Bayesian neural nets via local linearization
AISTATS 2021poster
The generalized Gauss-Newton (GGN) approximation is often used to make practical Bayesian deep learning approaches scalable by replacing a second order derivative with a product of first order derivatives. In this paper we argue that the GGN approximation should be understood as a local linearizatio…