Stochastic fluid dynamics extends classical fluid mechanics by incorporating randomness and uncertainty directly into the governing equations. This approach utilises stochastic differential equations ...
Backward stochastic differential equations (BSDEs) have emerged as a pivotal mathematical tool in the analysis of complex systems across finance, physics and engineering. Their formulation, generally ...
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 paper represents a generalization of the stability result on the Euler-Maruyama solution, which is established in the paper M. Milošević, Almost sure exponential stability of solutions to highly ...
Join the Mathematics Department Colloquia for a lecture with Professeur Nils Berglund from the Institut Denis Poisson, Universite d'Orleans. In this talk, we will consider parabolic stochastic partial ...
The Annals of Probability, Vol. 34, No. 2 (Mar., 2006), pp. 663-727 (65 pages) We develop a new method to uniquely solve a large class of heat equations, so-called Kolmogorov equations in infinitely ...
This course gives an introduction to how to create genetic circuit models. These models leverage chemical reactions represented using the Systems Biology Markup Language (SBML). The second module ...
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