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Efficient variational Bayesian neural network ensembles for outlier detection

2017-03-20Code Available0· sign in to hype

Nick Pawlowski, Miguel Jaques, Ben Glocker

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Abstract

In this work we perform outlier detection using ensembles of neural networks obtained by variational approximation of the posterior in a Bayesian neural network setting. The variational parameters are obtained by sampling from the true posterior by gradient descent. We show our outlier detection results are comparable to those obtained using other efficient ensembling methods.

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