Yeah I've used those methods and am a fan, though they are far from perfect. For one thing they're somewhat invasive methods to implement and they still require

Yeah I've used those methods and am a fan, though they are far from perfect. For one thing they're somewhat invasive methods to implement and they still require you to formulate a likelihood function to varying degrees; a task which is not always possible up front. I've also had issues with getting them to converge during training when using them. They also sometimes don't estimate uncertainty correctly, particularly if you make a mistake modeling the likelihood. I guess my point is, there is no silver bullet. Adding defensible uncertainty is complicated and problem specific, and comes with downsides (often steep).