Nicolò Botteghi

Deep invertible autoencoders for dimensionality reduction of dynamical systems

Constructing reduced-order models (ROMs) capable of efficiently predicting the evolution of parameter-dependent high-dimensional dynamical systems is crucial in many applications in engineering and applied sciences. A popular class of projection-based ROMs projects the high-dimen...