Ensemble Model Patching: A Parameter-Efficient Variational Bayesian Neural Network

23 May 2019Oscar ChangYuling YaoDavid Williams-KingHod Lipson

Two main obstacles preventing the widespread adoption of variational Bayesian neural networks are the high parameter overhead that makes them infeasible on large networks, and the difficulty of implementation, which can be thought of as "programming overhead." MC dropout [Gal and Ghahramani, 2016] is popular because it sidesteps these obstacles... (read more)

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