3 citations · 6 across the 4 of their papers we have counts for
4 papers
Liquid Fourier Latent Dynamics Networks for fast GPU-based numerical simulations in computational cardiology
Matteo Salvador, Alison L. Marsden
Scientific Machine Learning (ML) is gaining momentum as a cost-effective alternative to physics-based numerical solvers in many engineering applications. In fact, scientific ML is…
Neural active manifolds: nonlinear dimensionality reduction for uncertainty quantification
Andrea Zanoni, Gianluca Geraci, Matteo Salvador +2
We present a new approach for nonlinear dimensionality reduction, specifically designed for computationally expensive mathematical models. We leverage autoencoders to discover a on…
Improved multifidelity Monte Carlo estimators based on normalizing flows and dimensionality reduction techniques
Andrea Zanoni, Gianluca Geraci, Matteo Salvador +3
We study the problem of multifidelity uncertainty propagation for computationally expensive models. In particular, we consider the general setting where the high-fidelity and low-f…
A Modular Framework for Implicit 3D-0D Coupling in Cardiac Mechanics
Aaron L. Brown, Matteo Salvador, Lei Shi +6
In numerical simulations of cardiac mechanics, coupling the heart to a model of the circulatory system is essential for capturing physiological cardiac behavior. A popular and effi…