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. Suppose one wants to approximate the joint density of outputs and parameters . Bayes' formula reads:

:

The joint is equal to the product of the likelihood and the prior and by Bayes' rule, equal to the product of the marginal likelihood and posterior . Seen as a function of the joint is an un-normalised density.

In Laplace's approximation, we approximate the joint by an un-normalised

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