124 citations · 124 across the 4 of their papers we have counts for
4 papers · 1 filter
An iterative multi-fidelity approach for model order reduction of multi-dimensional input parametric PDE systems
Manisha Chetry, Domenico Borzacchiello, Lucas Lestandi +1
We propose a parametric sampling strategy for the reduction of large-scale PDE systems with multidimensional input parametric spaces by leveraging models of different fidelity. The…
Sensitivity analysis using Physics-informed neural networks
John M. Hanna, José V. Aguado, Sebastien Comas-Cardona +2
The goal of this paper is to provide a simple approach to perform local sensitivity analysis using Physics-informed neural networks (PINN). The main idea lies in adding a new term…
Residual-based adaptivity for two-phase flow simulation in porous media using Physics-informed Neural Networks
John M. Hanna, Jose V. Aguado, Sebastien Comas-Cardona +2
This paper aims to provide a machine learning framework to simulate two-phase flow in porous media. The proposed algorithm is based on Physics-informed neural networks (PINN). A no…
Sparse data-driven quadrature rules via -quasi-norm minimization
Mattia Manucci, Jose Vicente Aguado, Domenico Borzacchiello
In this paper we show the use of the focal underdetermined system solver to recover sparse empirical quadrature rules for parametrized integrals from existing data, consisting of t…