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Currently, the posterior module lives at the same level as the model module. The reasoning was that the same model (prior*likelihood) can have different posteriors depending on the inference method we choose (e.g. MAP, Laplace, Langevin, ...)
A more intuitive way to think of posterior may be to think of it as a trained model and move it to model.
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enhancementNew feature or requestNew feature or request