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Let‘s assume that I have a Poisson distribution with gamma=10. I would like to fit a Gaussian distribution, which minimizes KL divergence to the Poisson distribution. This is possible with variational inference. How can I use Stan to do this optimization?

The reference manual has a chapter on VI but only provides some high level information on how it is implemented internally, not how to use it.

The user guide mentions VI in chapter 22.2 but only with some general remarks on its efficiency.

A related question here on SO might be: Variational inference in PyStan API?

But that only asks whether advi has been implemented in PyStan (it has). There is no additional information.

lhk
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CmdStanPy contains an example notebook:

Mitzi Morris
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