Bayesian nonparametric methods include machine-learning and deep-learning methods as special cases, obtained by making quite coarse approximations to make the computation feasible. Using the fully fledged Bayesian method would give much more, but would take orders of magnitude more computational resources and time.

Papers like this, however, open up many more possibilities to use the full theory rather than approximations. I'm quite surprised to see that this paper is already four years old. I wonder if there's been any progress since then.