1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics
Simone Brugiapaglia, Nick Dexter, Samir Karam +1
On the forefront of scientific computing, Deep Learning (DL), i.e., machine learning with Deep Neural Networks (DNNs), has emerged a powerful new tool for solving Partial Different…
math.NA2022
Compressive Fourier collocation methods for high-dimensional diffusion equations with periodic boundary conditions
Weiqi Wang, Simone Brugiapaglia
High-dimensional Partial Differential Equations (PDEs) are a popular mathematical modelling tool, with applications ranging from finance to computational chemistry. However, standa…
math.NA2018
A compressive spectral collocation method for the diffusion equation under the restricted isometry property
Simone Brugiapaglia
We propose a compressive spectral collocation method for the numerical approximation of Partial Differential Equations (PDEs). The approach is based on a spectral Sturm-Liouville a…