SELF-SUPERVISED ADAPTIVE NETWORKS

A scheme for training multilayer unsupervised networks is presented, in which control signals propagate downwards from the higher layers to influence the optimisation of the lower layers. Because there is no external teacher involved, this is called self-supervised training. The author demonstrates both theoretically and numerically how self-supervision emerges when a simple network built out of vector quantisers is optimised.