I answered this in another post as well but this is straight up misinforming. Generative models do not necessarily know P(X,Y), often they simply give samples

I answered this in another post as well but this is straight up misinforming. Generative models do not necessarily know P(X,Y), often they simply give samples of (X,Y) using some map G: Q -> (X,Y); Q~N(0,1) Actually getting P(X,Y) would mean inverting G, which is not always possible (although there are some invertible GANs). Computing P(X) is often computationally intractable as tracing out variables can be arbitrarily expensive.