Deep Learning, Artificial Intelligence, Self Supervised Learning, Clustering, Contrastive Learning.
measures the fit between features z and a code q. In SwAV, first the “codes” are obtained by assigning features to prototype vectors. Then, a “swapped” prediction problem is solved wherein the codes obtained from one data augmented view are predicted using the other view. Thus, SwAV does not