This paper analyzes a high-accuracy approximation to the $m$th-order linear ordinary differential equation $Mu = f$.

Thanks to these abilities, they can already topple complex linear differential equations exponentially faster than classical machines. Researchers have long hoped they could similarly tame nonlinear ...

This paper is concerned with the numerical approximation of some linear stochastic partial differential equations with additive noises. A special representation of the noise is considered, and it is ...