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What is the difference between an input and observed data in a Bayesian neural network?
I'm new to the Bayesian perspective and would appreciate clarity on this.
In a few resources concerning Bayesian deep learning (such as this one), I see this notation:
$p(y|x, D) = \int p(y|x, \theta)...
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