Functional Variational Inference based on Stochastic Process Generators

Bayesian inference in the space of functions has been an important topic for Bayesian modeling in the past. In this paper, we propose a new solution to this problem called Functional V ariational Inference (FVI). In FVI, we minimize a divergence in function space between the variational distribution and the posterior process.