Disentangling the Gauss-Newton Method and Approximate Inference for Neural Networks

21 Jul 2020 Alexander Immer

In this thesis, we disentangle the generalized Gauss-Newton and approximate inference for Bayesian deep learning. The generalized Gauss-Newton method is an optimization method that is used in several popular Bayesian deep learning algorithms... (read more)

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