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Bayesian inference tells us that the posterior over parameters $\theta$ given data $X$ is given by:

$$p(\theta|X) = \frac{p(X|\theta)}{p(X)} p(\theta)$$

Are there any known bounds on the ratio of the likelihood divided by marginal $\frac{p(X|\theta)}{p(X)}$?

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