On the latent dimension of deep autoencoders for reduced order modeling of PDEs parametrized by random fields

Nicola Rares Franco, Daniel Fraulin, Andrea Manzoni +1

Deep Learning is having a remarkable impact on the design of Reduced Order Models (ROMs) for Partial Differential Equations (PDEs), where it is exploited as a powerful tool for tac…