Hi all gamers,

I’m wondering that when doing inference with edward, do we have to feed all variables in the graphical model into the inference instance?

For example with linear regression, y = a*x+b, the common inference would be:

ed.KLqp({a:qa, b:qb},data={x:x_data, y:y_data})

and we’ll get the approximated posterior for parameters a and b. But what if we only care about a? could we just define some prior over latent variable b and NOT feed it into the inference so it looks like this

ed.KLqp({a:qa},data={x:x_data, y:y_data})

So to conclude my question is would the above inferences give me similar/same qa for approximating posterior of parameter a?

Thanks !