This paper studies a new and highly efficient Markov chain Monte Carlo (MCMC)
methodology to perform Bayesian inference in low-photon imaging problems, with particular …

In this paper, we focus on nonasymptotic bounds related to the Euler scheme of an ergodic
diffusion with a possibly multiplicative diffusion term (nonconstant diffusion coefficient). More …

We study Poisson equations and averaging for Stochastic Differential Equations (SDEs).
Poisson equations are essential tools in both probability theory and partial differential …

We present a criterion for uniform in time convergence of the weak error of the Euler scheme
for Stochastic Differential equations (SDEs). The criterion requires (i) exponential decay in …

We study a population of N particles, which evolve according to a diffusion process and
interact through a dynamical network. In turn, the evolution of the network is coupled to the …

We introduce and analyse a continuum model for an interacting particle system of Vicsek
type. The model is given by a non-linear kinetic partial differential equation (PDE) describing …

We provide a Lyapunov convergence analysis for time-inhomogeneous variable coefficient
stochastic differential equations (SDEs). Three typical examples include overdamped …

We prove that incompressible two-dimensional nonequilibrium Langevin dynamics (NELD)
converges exponentially fast to a steady-state limit cycle. We use automorphism remapping …

First, we propose using rotating periodic boundary conditions (PBCs)[13] to simulate
nonequilibrium molecular dynamics (NEMD) in uniaxial or biaxial stretching flow. These …

This thesis is concerned with the analytical study of non-linear partial differential equations
(PDEs) of kinetic type which admit multiple stationary solutions. We consider a kinetic model …