SOURCE-LINKED INTELLIGENCE

Single State Update Predictive Coding training for Time Series Forecasting and Anomaly Detection

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Predictive Coding (PC) is a neural learning paradigm that enables parallelizable neural network layer updates. However, the main bottleneck of PC Networks (PCN) is the sequential backwards error propagation. To tackle this, we introduce a training technique that pairs a Generative PCN with a support Encoding PCN. The two PCNs are trained in parallel to match their neural activations, without sequential propagation. We apply this to time series anomaly detection and show that our approach results in more stable, continuous, online learning.

Read original source ↗ Open in workspace

recordType

paper

region

Global