Improving predictions of Bayesian neural nets via local linearization

Alexander Immer, Maciej Korzepa, Matthias Bauer

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…