You can take many equivalent perspectives on learning systems, but mostly it reduces to "messing with denominators in Bayes' rule". This is no different.

EBMs today aren't used because first you have to fit the joint model, then you have to fix some inputs, then fit the other inputs in a second optimization step. That's just too much compute for today's workloads compared to feedforward NNs.