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Deconstructing Predictive Coding Networks

Explore the biology of belief, local energy minimization, and pure PyTorch implementations of biologically plausible learning without backpropagation.

Part 1

Biology of Belief

Rethinking backpropagation through the lens of top-down predictions, local prediction errors, and Hebbian energy minimization.

Part 2

PyTorch Implementation

Building PCN inference loops and local Hebbian weight updates from scratch in pure PyTorch — no loss.backward() required.
View Code on GitHub

Part 3

Benchmark Showdown

Pitting the biological PCN against a standard MLP on nonlinear regression and MNIST classification to reveal the cost of biological plausibility.