A broad class of implicit or partially implicit time discretizations for the Langevin diffusion are considered and used as proposals for the Metropolis–Hastings algorithm. Ergodic properties of our proposed schemes are studied. We show that introducing implicitness in the discretization leads to a process that often inherits the convergence rate of the continuous time process. These contrast with the behavior of the naive or Euler–Maruyama discretization, which can behave badly even in simple cases. We also show that our proposed chains, when used as proposals for the Metropolis–Hastings algorithm, preserve geometric ergodicity of their implicit Langevin schemes and thus behave better than the local linearization of the Langevin diffusion. ...
International audienceIn this article, we consider the problem of sampling from a probability measur...
International audienceWe investigate a weighted Multilevel Richardson-Romberg extrapolation for the ...
Recent optimal scaling theory has produced a condition for the asymptotically optimal acceptance rat...
A broad class of implicit or partially implicit time discretizations for the Langevin diffusion are ...
We describe a Langevin diffusion with a target stationary density with respect to Lebesgue measure, ...
The Metropolis-adjusted Langevin (MALA) algorithm is a sampling algorithm which makes local moves by...
We consider a class of adaptive MCMC algorithms using a Langevin-type proposal density. We prove th...
In our work we propose new Exact Algorithms for simulation of diffusions with discontinuous drift an...
We consider a class of Langevin diffusions with state-dependent volatility. The volatility of the di...
We present and study a Langevin MCMC approach for sampling nonlinear diffusion bridges. The method i...
For sampling from a log-concave density, we study implicit integrators resulting from θ- method disc...
We describe a new MCMC method optimized for the sampling of probability measures on Hilbert space wh...
This paper proposes a new sampling scheme based on Langevin dynamics that is applicable within pseud...
We study an overdamped Langevin equation on the $d$-dimensional torus with stationary distribution p...
This thesis focuses on the analysis and design of Markov chain Monte Carlo (MCMC) methods used in hi...
International audienceIn this article, we consider the problem of sampling from a probability measur...
International audienceWe investigate a weighted Multilevel Richardson-Romberg extrapolation for the ...
Recent optimal scaling theory has produced a condition for the asymptotically optimal acceptance rat...
A broad class of implicit or partially implicit time discretizations for the Langevin diffusion are ...
We describe a Langevin diffusion with a target stationary density with respect to Lebesgue measure, ...
The Metropolis-adjusted Langevin (MALA) algorithm is a sampling algorithm which makes local moves by...
We consider a class of adaptive MCMC algorithms using a Langevin-type proposal density. We prove th...
In our work we propose new Exact Algorithms for simulation of diffusions with discontinuous drift an...
We consider a class of Langevin diffusions with state-dependent volatility. The volatility of the di...
We present and study a Langevin MCMC approach for sampling nonlinear diffusion bridges. The method i...
For sampling from a log-concave density, we study implicit integrators resulting from θ- method disc...
We describe a new MCMC method optimized for the sampling of probability measures on Hilbert space wh...
This paper proposes a new sampling scheme based on Langevin dynamics that is applicable within pseud...
We study an overdamped Langevin equation on the $d$-dimensional torus with stationary distribution p...
This thesis focuses on the analysis and design of Markov chain Monte Carlo (MCMC) methods used in hi...
International audienceIn this article, we consider the problem of sampling from a probability measur...
International audienceWe investigate a weighted Multilevel Richardson-Romberg extrapolation for the ...
Recent optimal scaling theory has produced a condition for the asymptotically optimal acceptance rat...