Physics-informed neural network estimation of material properties in soft tissue nonlinear biomechanical models

F Caforio, F Regazzoni, S Pagani, E Karabelas… - Computational …, 2024 - Springer
The development of biophysical models for clinical applications is rapidly advancing in the
research community, thanks to their predictive nature and their ability to assist the …

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

NR Franco, D Fraulin, A Manzoni, P Zunino - Advances in Computational …, 2024 - Springer
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 …