a noise distribution that is gaussian as the reference distribution then in practice learning tends to slow down relatively quickly once the generator once the model has learned to create samples that are easily distinguishable from a Gaussian in maximum likelihood estimation we take the parameters of the model distribution and we copy them into the noise distribution and we do this before each step begins so in some ways the maximum likelihood estimation procedure can be seen as the model constantly trying to