Papers

Here is a list of papers and pre-prints. The following is our recent work on privacy, more to come

Bayesian Adversarial Privacy
Cameron Bell, Timothy Johnston, Antoine Luciano, Christian P Robert
https://arxiv.org/abs/2603.04199

And these works on singular SDEs, also more to come

A tamed Euler scheme for SDEs with non-locally integrable drift coefficient
Tim Johnston, Sotirios Sabanis
Stochastic Processes and their Applications (2026)

A Lyapunov-Tamed Euler Method for Singular SDEs
Tim Johnston, Pierre Monmarché
https://arxiv.org/abs/2601.16878

And then finally these papers are on SDEs and Markov Chains

Differential privacy guarantees of Markov chain Monte Carlo algorithms
Andrea Bertazzi, Tim Johnston, Gareth Roberts, Alain Durmus
ICML 2025

Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation
Omer Deniz Akyıldız, Francesca Romana Crucinio, Mark Girolami, Tim Johnston, Sotirios Sabanis
ESAIM: Probability & Statistics 29 (2025)

Taming the Interactive Particle Langevin Algorithm - the superlinear case
Tim Johnston, Nikos Makras, Sotirios Sabanis
Applied Mathematics & Optimization. 91 (2025)

The Performance Of The Unadjusted Langevin Algorithm Without Smoothness Assumptions Tim Johnston, Iosif Lytras, Nikos Makras, Sotirios Sabanis
Transactions on Machine Learning Research (2025)

A Strongly Monotonic Polygonal Euler Scheme
Tim Johnston, Sotirios Sabanis
Journal of Complexity 80 (2024)

Kinetic Langevin MCMC Sampling Without Gradient Lipschitz Continuity
Tim Johnston, Iosif Lytras, Sotirios Sabanis
Journal of Complexity 85 (2024)