Recurrent predictive coding models for associative memory employing covariance learning
Fig 4
Performance of the single-layer covPCNs in AM of structured images.
A: Examples of retrieved MNIST (top) [19] and grayscale CIFAR10 (bottom)[20] images by explicit, implicit and dendritic models. All models here are trained to memorize 64 images. For MNIST, the networks have d = 784 neurons; for grayscale CIFAR10, d = 1024. B: Retrieval mean squared errors (MSEs) of the single-layer models across multiple numbers of training memories (N). C: Evolution of the retrieval MSEs of the implicit and dendritic models when N = 256. D: Example eigenspectra of the weight matrices defining the inferential dynamics for the dendritic (left) and implicit (right) covPCNs. Error bars obtained by 5 different seeds for image sampling. Please see main text for an explanation of the matrix M.