Slim multi-scale convolutional autoencoder-based reduced-order models for interpretable features of a complex dynamical system

Philipp Teutsch, Philipp Pfeffer, Mohammad Sharifi Ghazijahani +3

In recent years, data-driven deep learning models have gained significant interest in the analysis of turbulent dynamical systems. Within the context of reduced-order models (ROMs)…