Machine Learning, Generative Model, Bayesian Machine Learning.
between the true and generated examples to be differentiable, regardless of whether the true and currently-being-generated distributions had the same support over X. This was crucially important, because, in prior versions of GANs, the discriminator had simply been outputting a probability of the