We study in this paper weak approximations in Wasserstein-1 distance to stochastic variance reduced gradient Langevin dynamics by stochastic delay differential equations, and obtain uniform error bounds. Our approach is via Malliavin calculus and a refined Lindeberg principle
International audienceWe deal with stochastic differential equations with jumps. In order to obtain ...
To our knowledge, existing measure approximation theory requires the diffusion term of the stochasti...
AbstractThe paper deals with weak approximations of stochastic differential equations of Itô type, w...
In this paper, we focus on non-asymptotic bounds related to the Euler scheme of an ergodic diffusion...
In this paper, we develop a strong Milstein approximation scheme for solving stochastic delay differ...
AbstractWe consider stochastic delay systems dx(t) = g(x(t − r)) dW(t) driven by multi-dimensional B...
International audienceIn this article we develop a new methodology to prove weak approximation resul...
We establish generalization error bounds for stochastic gradient Langevin dynamics (SGLD) with const...
In this paper, we develop a strong Milstein approximation scheme for solving stochastic delay differ...
In this paper, we are concerned with a non-asymptotic analysis of sampling algorithms used in noncon...
We present a framework that allows for the non-asymptotic study of the 2 -Wasserstein distance betw...
International audienceIn this article, we consider the problem of sampling from a probability measur...
The goal of this paper is to present a series of recent contributions arising in numerical probabili...
We establish a sharp uniform-in-time error estimate for the Stochastic Gradient Langevin Dynamics (S...
It is well-known that under suitable conditions there exists a unique solution of a ddimensional lin...
International audienceWe deal with stochastic differential equations with jumps. In order to obtain ...
To our knowledge, existing measure approximation theory requires the diffusion term of the stochasti...
AbstractThe paper deals with weak approximations of stochastic differential equations of Itô type, w...
In this paper, we focus on non-asymptotic bounds related to the Euler scheme of an ergodic diffusion...
In this paper, we develop a strong Milstein approximation scheme for solving stochastic delay differ...
AbstractWe consider stochastic delay systems dx(t) = g(x(t − r)) dW(t) driven by multi-dimensional B...
International audienceIn this article we develop a new methodology to prove weak approximation resul...
We establish generalization error bounds for stochastic gradient Langevin dynamics (SGLD) with const...
In this paper, we develop a strong Milstein approximation scheme for solving stochastic delay differ...
In this paper, we are concerned with a non-asymptotic analysis of sampling algorithms used in noncon...
We present a framework that allows for the non-asymptotic study of the 2 -Wasserstein distance betw...
International audienceIn this article, we consider the problem of sampling from a probability measur...
The goal of this paper is to present a series of recent contributions arising in numerical probabili...
We establish a sharp uniform-in-time error estimate for the Stochastic Gradient Langevin Dynamics (S...
It is well-known that under suitable conditions there exists a unique solution of a ddimensional lin...
International audienceWe deal with stochastic differential equations with jumps. In order to obtain ...
To our knowledge, existing measure approximation theory requires the diffusion term of the stochasti...
AbstractThe paper deals with weak approximations of stochastic differential equations of Itô type, w...