Deep Learning, Machine Learning, Self Supervised Learning, Aritificial Intelligence, Neural Networks.
number of prototypes K, it is impossible to equally partition the batch into the K prototypes. Therefore, when working with small batches, the authors use features from the previous batches to augment the size of Z in (3), and only the codes of the batch features are used in the training loss. The