On Representing Prior Information as an Asymmetric Prior Distribution over Weights

Abstract

The Bayesian modeling formalism provides a principled means of incorporating prior information into a neural network model. One can extract greater power from the Bayesian formalism through use of priors which encode particular empirical or expert knowledge. These priors will generally be asymmetric with respect to the neural network output function. It… (More)

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