An effective approach to solving sparse regularization problems is the iterative re-weighting least squares (IRLSs) algorithm. However, IRLS is computationally intensive and may not be suitable for ...

Finite basis physics-informed neural networks (FBPINNs) This repository allows you to solve forward and inverse problems related to partial differential equations (PDEs) using finite basis ...

We consider dynamic evaluation of algebraic functions such as computing determinant, matrix adjoint, matrix inverse and solving linear system of equations. We show that in the dynamic setup the above ...

In particular, the proposed method simultaneously faces the model solution and the parameter identification, leveraging the linear dependency between the terms of the governing equations and then ...

These solvers are not recommended for large order matrices. Based on the conjugate gradient method to solve linear systems or least-squares problems, several iterative solvers have been implemented, ...