

Exploring the High-dimensional Random Landscapes of Data Science (3/3)
De Gérard Ben Arous


Exploring the High-dimensional Random Landscapes of Data Science (1/3)
De Gérard Ben Arous
De Dan Crisan
Apparaît dans les collections : CEMRACS - Summer school: Numerical methods for stochastic models: control, uncertainty quantification, mean-field / CEMRACS - École d'été : Méthodes numériques pour équations stochastiques : contrôle, incertitude, champ moyen, Ecoles de recherche
The talk will have two parts: In the first part, I will go over some of the basic feature of cubature methods for approximating solutions of classical SDEs and how they can be adapted to solve Backward SDEs. In the second part, I will introduce some recent results on the use of cubature method for approximating solutions of McKean-Vlasov SDEs.