Predictive Coding Graphs are a Superset of Feedforward Neural Networks
Predictive coding graphs (PCGs) are a recently introduced generalization to predictive coding networks, a neuroscience-inspired probabilistic latent variable model. Here, we prove how PCGs define a mathematical superset of feedforward artificial neural networks (multilayer perceptrons). This positions PCNs more strongly within contemporary machine learning (ML), and reinforces earlier proposals to study the use of non-hierarchical neural networks for ML tasks, and more generally the notion of topology in neural networks.
| Authors | Björn van Zwol |
|---|---|
| Primary category | cs.LG |
| Published | 6 March 2026 |
| Last updated at source | 6 March 2026 |
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