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The MNLE classes are now refactored to match the API of the other build functions, including z-scoring and embedding nets. Thus, in principle, one can now also use the MNLE setup for posterior inference. However, it allows only for a single discrete column in x (theta).
An autoregressive density estimator on top would be the solution, see #1112
For discrete (mixed) parameters.
Can probably recycle a lot of code from MNLE.
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