The Laplace approximation method is a technique used to approximate complex probability distributions—especially posterior distributions in Bayesian inference—by a Gaussian distribution centered at the mode (typically the MAP estimate).
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Laplace's method fits a gaussian to any possible (hard, unnormalized) distribution.
