resembles the process of minimizing the Jensen's Shannon divergence between the data and the model we can use that to actually prove that we'll recover the correct data distribution if we go to the equilibrium of the game we can analyze what the discriminator does and they play this game and we see exactly what it is that allows generative adversarial networks to be effective the basic idea is that if you take the derivatives of the minimax games value function with respect to the outputs of the discriminator we can actually solve