50 citations · 61 across the 12 of their papers we have counts for
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cs.LG2023
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…
cs.LG2021★ 7 cited
Learning High-Order Interactions via Targeted Pattern Search
Michela C. Massi, Nicola R. Franco, Francesca Ieva +3
Logistic Regression (LR) is a widely used statistical method in empirical binary classification studies. However, real-life scenarios oftentimes share complexities that prevent fro…