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Eigenvalue Corrected Noisy Natural Gradient
[article]
2018
arXiv
pre-print
Variational Bayesian neural networks combine the flexibility of deep learning with Bayesian uncertainty estimation. However, inference procedures for flexible variational posteriors are computationally expensive. A recently proposed method, noisy natural gradient, is a surprisingly simple method to fit expressive posteriors by adding weight noise to regular natural gradient updates. Noisy K-FAC is an instance of noisy natural gradient that fits a matrix-variate Gaussian posterior with minor
arXiv:1811.12565v1
fatcat:qp37ticqxbc65et4pzuhwk5kxu