Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning

1 Jul 2019Sebastian FarquharMichael OsborneYarin Gal

We propose Radial Bayesian Neural Networks (BNNs): a variational approximate posterior for BNNs which scales well to large models while maintaining a distribution over weight-space with full support. Other scalable Bayesian deep learning methods, like MC dropout or deep ensembles, have discrete support-they assign zero probability to almost all of the weight-space... (read more)

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