Numerical methods for stochastic differential equations with applications to molecular modelling and statistical inference (Ben Leimkuhler, Edinburgh)

24.04.2018 14:00

Molecular models and data analytics problems give rise to large systems of stochastic differential equations (SDEs) whose paths ergodically sample multimodal probability distributions. An important challenge for the numerical analyst (or the chemist, or the physicist, or the engineer, or the data scientist) is the design of efficient numerical methods to generate these paths. For SDEs, the numerical perspective is just maturing, with important new methods (and, even more important, new procedures for their construction and analysis) becoming available. I will discuss examples of efficient schemes for stochastic sampling dynamics arising in our work. I will also touch on the interplay between numerical schemes arising in physical and statistical contexts.


salle 623, Séminaire d'analyse numérique

Organisé par

Section de mathématiques


Ben Leimkuhler, University of Edinburgh

entrée libre


Catégorie: Séminaire

Mots clés: analyse numérique