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 ...

Stochastic fluid dynamics extends classical fluid mechanics by incorporating randomness and uncertainty directly into the governing equations. This approach utilises stochastic differential equations ...

Professor Franco Flandoli from the Scuola Normale Superiore di Pisa in Italy will give a series of lectures on the stochastic partial differential equations in fluid mechanics. Stochastic ...

Professor Franco Flandoli from the Scuola Normale Superiore di Pisa in Italy will give a series of lectures on the stochastic partial differential equations in fluid mechanics. April 8 (Thurs.), 2021 ...

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 ...

Inspired by path integral solutions to the quantum relaxation problem, we develop a numerical method to solve classical stochastic differential equations with multiplicative noise that avoids ...

(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.

Department of Mathematics and Computer Science, Faculty of Technology and Computer Science, University Iba Der Thiam of Thiès, Thiès, Senegal. 1) Establishment of sufficient conditions for existence ...

Abstract: This note focuses on the dissipativity and stability of highly nonlinear hybrid stochastic differential delay equations (HSDDEs). Firstly, based on the results of previous research, a series ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...