I have a very simple toy recurrent neural network implemented in keras which, given an input of N integers will return their mean value. I would like to be able to modify this to a bayesian neural network with either pymc3 or edward.lib so that I can get a posterior distribution on the output value
e.g. p(output | weights).
I have read through blog posts from autograd, pymc3 and edward [1,2,3] but all seem geared to classification problems.
To clarify - I am asking if anyone can offer some experience/advice/references relevant to building a Bayesian RNN in anything other than a classification task.