Delay-Embedding-based Forecast Machine for Accurate Multistep-Ahead Prediction of High-Dimensional Chaotic Systems

The DEFM framework leverages deep neural networks to effectively extract both the spatially and temporally associated information from high-dimensional observed time series, enabling accurate multistep-ahead prediction of the future values of a target variable.