2 papers
math.NA2025
A reduced-order model for advection-dominated problems based on Radon Cumulative Distribution Transform
Tobias Long, Robert Barnett, Richard Jefferson-Loveday +2
Problems with dominant advection, discontinuities, travelling features, or shape variations are widespread in computational mechanics. However, classical linear model reduction and…
math.NA2024
Inverse Physics-Informed Neural Networks for transport models in porous materials
Marco Berardi, Fabio Difonzo, Matteo Icardi
Physics-Informed Neural Networks (PINN) are a machine learning tool that can be used to solve direct and inverse problems related to models described by Partial Differential Equati…