Dropout Inference in Bayesian Neural Networks with Alpha-divergences

ICML 2017 Yingzhen LiYarin Gal

To obtain uncertainty estimates with real-world Bayesian deep learning models, practical inference approximations are needed. Dropout variational inference (VI) for example has been used for machine vision and medical applications, but VI can severely underestimates model uncertainty... (read more)

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