with some of the other approaches and describing some of the overall goals in this area that we're working on the basic idea of generative modeling is to take a collection of training examples and form some representation of a probability distribution that explains where those training examples came from there are two basic things that you can do with a generative model one is you can take a collection of points and infer a density function that describes the probability distribution that generated them I show that in the upper