5 papers
Correcting Neural Operator Spectral Bias via Diffusion Posterior Sampling with Sparse Observations
Niccolò Perrone, Fanny Lehmann, Stefania Fresca +1
Neural operator surrogates (NO) approximate PDE solutions orders of magnitude faster than numerical solvers, but suffer from spectral bias: high-frequency content is systematically…
HypeRL: Hypernetwork-Based Reinforcement Learning for Control of Parametrized Dynamical Systems
Nicolò Botteghi, Stefania Fresca, Mengwu Guo +1
In this work, we devise a new, general-purpose reinforcement learning strategy for the optimal control of parametric dynamical systems. Such problems frequently arise in applied sc…
Explainable Deep Learning-based Classification of Wolff-Parkinson-White Electrocardiographic Signals
Alice Ragonesi, Stefania Fresca, Karli Gillette +3
Wolff-Parkinson-White (WPW) syndrome is a cardiac electrophysiology (EP) disorder caused by the presence of an accessory pathway (AP) that bypasses the atrioventricular node, faste…
On latent dynamics learning in nonlinear reduced order modeling
Nicola Farenga, Stefania Fresca, Simone Brivio +1
In this work, we present the novel mathematical framework of latent dynamics models (LDMs) for reduced order modeling of parameterized nonlinear time-dependent PDEs. Our framework…
Handling geometrical variability in nonlinear reduced order modeling through Continuous Geometry-Aware DL-ROMs
Simone Brivio, Stefania Fresca, Andrea Manzoni
Deep Learning-based Reduced Order Models (DL-ROMs) provide nowadays a well-established class of accurate surrogate models for complex physical systems described by parametrized PDE…