N. Tonicello

Convolutional Symmetric AutoEncoders: enhancing latent stability via differential geometry

G. Li Causi, N. Tonicello, L. Magri, G. Rozza

Autoencoders (AEs) have emerged as powerful tools for non-linear dimensionality reduction, often surpassing traditional linear methods such as Proper Orthogonal Decomposition (POD) in scenarios characterized by slowly decaying Kolmogorov $n$-widths. In the realm of Reduced-Order…Read more