Generic Models Besides GANS Are There?

Most generative models are likelihood based where to train them, you have a model that tells you how much probability it assigns to a particular example. One approach is to very carefully design the model so that it is computationally tractable to measure the density designs to a particular point. There are things like auto-regressive models like pixel CNN. Those basically break down the probability distribution into a product over every single feature. So for an image, you estimate the probability of each pixel given all of the pixels that came before it.