Predictive Coding Networks
PulseAugur coverage of Predictive Coding Networks — every cluster mentioning Predictive Coding Networks across labs, papers, and developer communities, ranked by signal.
-
New method enables training of very deep predictive coding networks
Researchers have introduced a new method called highway error propagation (HEP) to address the challenge of training very deep predictive coding networks (PCNs). Traditional PCNs struggle with learning signals decaying …
-
New Hopfield Network Variant Boosts Associative Memory Robustness
Researchers have introduced Convolutional Restricted Hopfield Networks (CRHNs) as a novel approach to associative memory, aiming to improve robustness against adversarial perturbations and input corruptions. Unlike exis…
-
Equilibrium Propagation scales to train large predictive coding networks on ImageNet
Researchers have developed a new method to train predictive coding networks (PCNs) using Equilibrium Propagation (EP), a physics-based framework. This novel approach successfully scaled EP and PCNs to train a 10-layer c…
-
Predictive Coding Networks match Backpropagation in theory
Researchers have theoretically analyzed the infinite width and depth limits of Predictive Coding Networks (PCNs), an alternative to standard backpropagation. Their findings indicate that for linear residual networks, PC…