study how much inﬂuence have speciﬁc data augmentations on SimCLR with respect
to the performances over ImageNet. They show that simpler data augmentation such
as noise aren’t beneﬁcial on ImageNet classiﬁcation downstream. Instead, cropping and
A Cookbook of Self-Supervised Learning