5 papers
A Lyapunov-tamed Euler method for singular SDEs
Tim Johnston, Pierre Monmarché
Many applications, such as systems of interacting particles in physics, require the simulation of diffusion processes with singular coefficients. Standard Euler schemes are then no…
The Performance Of The Unadjusted Langevin Algorithm Without Smoothness Assumptions
Tim Johnston, Iosif Lytras, Nikolaos Makras +1
In this article, we study the problem of sampling from distributions whose densities are not necessarily smooth nor logconcave. We propose a simple Langevin-based algorithm that do…
Differential privacy guarantees of Markov chain Monte Carlo algorithms
Andrea Bertazzi, Tim Johnston, Gareth O. Roberts +1
This paper aims to provide differential privacy (DP) guarantees for Markov chain Monte Carlo (MCMC) algorithms. In a first part, we establish DP guarantees on samples output by MCM…
Taming the Interacting Particle Langevin Algorithm: The Superlinear case
Tim Johnston, Nikolaos Makras, Sotirios Sabanis
Recent advances in stochastic optimization have yielded the interacting particle Langevin algorithm (IPLA), which leverages the notion of interacting particle systems (IPS) to effi…
Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
Ã. Deniz Akyildiz, Francesca Romana Crucinio, Mark Girolami +2
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 model.…