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

The development of quantum processors for practical fluid flow problems is a promising yet distant goal. Recent advances in quantum linear solvers have highlighted their potential for classical fluid ...

Abstract: We show that applying a generalization of the Cayley-Hamilton Theorem to a state-space representation of a single-output, multidimensional (mD), linear, shift-invariant, causal, autonomous ...