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I think there's a bit of a misunderstanding as to what we're doing in Bayesian neural networks.
We know there's a real posterior distribution over the weights given the data but that the distribution is intractable or too computationally expensive to compute. To solve this we're approximating this posterior distribution with some variational distribution ...
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