Machine Learning, Artificial Intelligence, Neural Networks, Data Science, Towards Data Science.
so you need to match expected value at training. With inverted dropout, scaling is applied at the training time, but inversely. First, dropout all activations by dropout factor p, and second, scale them by inverse dropout factor 1/p. Inverted dropout has an advantage, that you don’t have to do