The study of stochastic differential equations (SDEs) has long been a cornerstone in the modelling of complex systems affected by randomness. In recent years, the extension to G-Brownian motion has ...

This paper presents a novel and direct approach to solving boundary- and final-value problems, corresponding to barrier options, using forward pathwise deep learning and forward–backward stochastic ...

(Conditional) generative adversarial networks (GANs) have had great success in recent years, due to their ability to approximate (conditional) distributions over extremely high-dimensional spaces.

This is a preview. Log in through your library . Abstract We study the weak solution X of a parabolic stochastic partial differential equation driven by two independent processes: a Gaussian white ...

In this paper, we study the 2D stochastic quasi-geostrophic equation on 𝕋2 for general parameter α ∈ (0, 1) and multiplicative noise. We prove the existence of weak solutions and Markov selections ...