Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks

12 Dec 2019Beau CokerMelanie F. PradierFinale Doshi-Velez

While Bayesian neural networks have many appealing characteristics, current priors do not easily allow users to specify basic properties such as expected lengthscale or amplitude variance. In this work, we introduce Poisson Process Radial Basis Function Networks, a novel prior that is able to encode amplitude stationarity and input-dependent lengthscale... (read more)

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