In this article, we consider the problem of sampling from a probability measure π having a
density on R d proportional to x↦ e− U (x). The Euler discretization of the Langevin …

In this paper, we derive fully implementable first-order time-stepping schemes for McKean–
Vlasov stochastic differential equations, allowing for a drift term with super-linear growth in …

This article proposes and analyzes explicit and easily implementable temporal numerical
approximation schemes for additive noise-driven stochastic partial differential equations …

In this paper, we introduce fully implementable, adaptive Euler–Maruyama schemes for
McKean–Vlasov stochastic differential equations (SDEs) assuming only a standard …

In this paper, we first establish well-posedness of McKean–Vlasov stochastic differential
equations (McKean–Vlasov SDEs) with common noise, possibly with coefficients of super …

This paper focuses on two variants of the Milstein scheme, namely the split-step backward
Milstein method and a newly proposed projected Milstein scheme, applied to stochastic …

We develop a class of interacting particle systems for implementing a maximum marginal
likelihood estimation (MMLE) procedure to estimate the parameters of a latent variable …

We introduce an explicit Milstein-type scheme for McKean–Vlasov stochastic differential
equations using the notion of a measure derivative given by P.-L. Lions in his lectures at the …

In this article, we propose two types of explicit tamed Euler–Maruyama (EM) schemes for
neutral stochastic differential delay equations with superlinearly growing drift and diffusion …

We study pathwise approximation of scalar stochastic differential equations at a single time
point or globally in time by means of methods that are based on finitely many observations of …