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We investigate the benefit of treating all the parameters in a Bayesian neural network stochastically and find compelling theoretical and empirical evidence that this standard construction may be unnecessary.
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Disentangling the Roles of Curation, Data-Augmentation and the Prior in the Cold Posterior Effect
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Wide mean-field bayesian neural networks ignore the data
B. Coker, W. P. Bruinsma, D. R. Burt, W. Pan, and F. Doshi-Velez · 2022
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