Translations:Dropout A Simple Way to Prevent Overfitting/15/en

This weight scaling inference rule ensures that the expected output of each neuron at test time equals its expected output during training. An equivalent alternative, inverted dropout, scales activations by $ 1/p $ during training so that no modification is needed at test time. This approach is more common in modern implementations.