Research

Publications

1. Tamás P. Papp and Chris Sherlock, A new and asymptotically optimally contracting coupling for the random walk Metropolis, 2022 – arXiv
2. Tamás P. Papp and Chris Sherlock, Bounds on Wasserstein distances between continuous distributions using independent samples, 2022 – arXiv

PhD

Projects I have worked on include sensible debiasing for empirical Wasserstein distance estimates and the design of scalable couplings for unbiased Markov chain Monte Carlo (à la Jacob et al, 2020). My supervisor is Chris Sherlock.

MRes

I wrote my dissertation on methodology and theory for unbiased Markov chain Monte Carlo, supervised by Chris Sherlock. Much of my PhD research stems from preliminary work carried out there.

Three literature reviews I wrote during the MRes are available below:

1. Bayesian nonparametrics – supervised by Marco Battiston
2. Rate function estimation for non-homogeneous Poisson processes – supervised by Lucy Morgan
3. Multi-armed bandits and Bayesian optimisation – supervised by David S. Leslie

References

• Pierre E. Jacob, John O’Leary and Yves F. Atchadé, Unbiased Markov chain Monte Carlo methods with couplings – JRSS:B 82(3), 2020 (arXiv)