A new algorithm developed by Naoki Masuda, with co-athors Kazuyuki Aihara and Neil G. MacLaren, can identify the most predictive data points that a tipping point is near. Published ...

Descriptions ES_APPM 442-0: Stochastic Differential Equations VIEW ALL COURSE TIMES AND SESSIONS Description Brownian motion and Langevin's equation. Ito and Stratonovich Stochastic integrals.

Many dynamic processes can be described mathematically with the aid of stochastic partial differential equations. Scientists have found a new method which helps to solve a certain class of such ...

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 method uses deep learning and pathwise forward–backward stochastic differential equations to solve boundary value problems (eg, for barrier options) by adding nodes to the computational graph to ...

Using conditional neural stochastic differential equations, the authors propose a means to improve the efficiency of generative adversarial networks and test ...

ES_APPM 446-1: Numerical Solution of Partial Differential Equations VIEW ALL COURSE TIMES AND SESSIONS Description Introductory course on using a range of finite-difference methods to solve ...