Other self-supervised techniques like SimCLR, BYOL, SwAV etc. rely heavily on a well-designed data augmentation pipeline to get the best performance. However, NNCLR is less dependent on complex augmentations as nearest-neighbors already provide richness in sample variations. A few common techniques often included augmentation pipelines are: