I’m not sure if you are aware, but Bayesian neural networks can be actually be well approximated by appropriate ensembles of standard neural networks [0]. The strength of Bayesian nets (including the approximating ensembles) is that they are able to estimate the uncertainty in their own predictions (by generating a probability distribution of possible predictions), at the cost of more computation needed for training and inference. I don’t think it’s ever going to be a matter of Bayesian nets outright outcompeting standard nets though, it’s just another tool in the toolbox if you want a model which “knows it doesn’t know something” and don’t mind the extra compute needed.