Energy-based models are superior to standard neural networks because they optimize both weights and internal latent states, effectively incorporating constraints that act as inductive priors.

“the advantage of using an energy based uh taking an energy based approach as opposed to taking say a straight up like function approximation approach is that an energy based model comes with something that's kind of like an inductive prior”