Retrieval-Augmented Forecasting: Improving Time-Series Model Accuracy

Retrieval-Augmented Forecasting (RAF) is revolutionizing time-series analysis by adding an explicit memory step to traditional models. Instead of relying on static training weights, RAF allows models to perform similarity searches on historical data, significantly improving accuracy during rare events and market shifts. Learn how to implement vector-based memory for more robust forecasting.