Vector valued parameters about bayem HOT 3 CLOSED

I would say those are two separate questions. The general interface should allow this, the restriction you mention all relate to our VB implementation (with optional options to work on all the issues you mentioned above). Thus, if our VB is just a single inference solver, the vector parameter approach would generally be very helpful, e.g. I had a problem with model bias being modelled by a correlated Gaussian process, and all the amplitudes at the training points where random variables. For sure, this works only for small problems with the currently implemented inference solvers, but a parameter vector would be very convenient.

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Another application is a random field, so the model parameters are the individual parameters (spatially variable, but correlated).

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Further discussed here BAMresearch/probeye#2

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