Introduction to Predictive Coding Networks for Machine Learning
Journal:
arXiv
Published Date:
May 31, 2025
Abstract
Predictive coding networks (PCNs) constitute a biologically inspired
framework for understanding hierarchical computation in the brain, and offer an
alternative to traditional feedforward neural networks in ML. This note serves
as a quick, onboarding introduction to PCNs for machine learning practitioners.
We cover the foundational network architecture, inference and learning update
rules, and algorithmic implementation. A concrete image-classification task
(CIFAR-10) is provided as a benchmark-smashing application, together with an
accompanying Python notebook containing the PyTorch implementation.
