> Pyro enables flexible and expressive deep probabilistic modeling, unifying the best of modern deep learning and Bayesian modeling.
Does anyone who works in this area have a sense of why PPLs haven't "taken off" really? Like, of the last several years of ML surprising successes, I can't really think of any major ones that come from this line of work. To the extent that Bayesian perspectives contribute to deep learning, I more often see e.g. some particular take on ensembling around the same models trained to find a point estimate via SGD, rather than models built up from random variables about which we update beliefs including representation of uncertainty.
Does anyone who works in this area have a sense of why PPLs haven't "taken off" really? Like, of the last several years of ML surprising successes, I can't really think of any major ones that come from this line of work. To the extent that Bayesian perspectives contribute to deep learning, I more often see e.g. some particular take on ensembling around the same models trained to find a point estimate via SGD, rather than models built up from random variables about which we update beliefs including representation of uncertainty.