Hi!

I want to run an outside optimization routine using python. Trying both variational inference or hamiltonian monte carlo. I imagine there must be a way to do this, but I was wondering if there was an easy way to solve a model then return both the likelihood and the gradient, so I can pass that to the python code. I would prefer analytic gradients using analytical derivation but would be fine either way.

Thanks,

Cameron