normalizing statistics unfortunately because we always use the same images we can start to overfit to that particular reference batch to partially resolve that we introduced a technique called virtual batch normalization the basic idea here is that every time you want to normal as an example X we normalize it using statistics computed both on the reference batch and on the example X itself added to that batch a lot of people ask me questions about how to balance the generator and the discriminator and if they need to be