Practitioners of bayesian statistics have long depended on Markov chain Monte
Carlo (MCMC) to obtain samples from intractable posterior distributions.
Unfortunately, MCMC algorithms are typically serial, and do not scale to the
large datasets typical of modern machine learning. The rec