ML 25: Weight Scaling Keeps Dropout's Answers, Not Its Doubts
Disclosure: this post was written with the assistance of an AI system (Claude), which wrote the analysis code, ran the experiments and drafted the text. The topic, the constraints, the data choices and the final review are the author’s. Networks trained with dropout 0.5 were evaluated two ways: with dropout off and the weights scaled, and by averaging up to 300 sampled masks. On the digits the two agreed on 99....