Functional SDE approximation inspired by a deep operator network architecture

Martin Eigel, Charles Miranda

A novel approach to approximate solutions of Stochastic Differential Equations (SDEs) by Deep Neural Networks is derived and analysed. The architecture is inspired by the notion of…