K. Latuszy'nski

Adaptive Gibbs samplers and related MCMC methods

J. Rosenthal, G. Roberts, K. Latuszy'nski, 2011, 1101.5838.

Nonasymptotic bounds on the estimation error of MCMC algorithms

K. Latuszy'nski, Wojciech Niemiro, B. Miasojedow, 2011, 1106.4739.

Convergence of hybrid slice sampling via spectral gap

K. Latuszy'nski, D. Rudolf, Daniel Rudolf, 2014, 1409.2709.

Stability of adversarial Markov chains, with an application to adaptive MCMC algorithms

Gareth O. Roberts, Neal Madras, Radu V. Craiu, 2014 .

Perfect simulation using atomic regeneration with application to Sequential Monte Carlo

Arnaud Doucet, Anthony Lee, Krzysztof Latuszy'nski, 2014, 1407.5770.

Barker's algorithm for Bayesian inference with intractable likelihoods

Gareth O. Roberts, Flavio B. Gonccalves, Krzysztof Latuszy'nski, 2017 .

Optimal scaling of MCMC beyond Metropolis

Gareth O. Roberts, Dootika Vats, Sanket Agrawal, 2021, Advances in Applied Probability.

Stereographic Markov Chain Monte Carlo

G. Roberts, K. Latuszy'nski, Jun Yang, 2022, 2205.12112.

A framework for adaptive MCMC targeting multimodal distributions

C. Holmes, K. Latuszy'nski, E. Pompe, 2018, The Annals of Statistics.

Solidarity of Gibbs Samplers: the spectral gap

K. Latuszy'nski, B. Miasojedow, I. Chlebicka, 2023, 2304.02109.

Bayesian computation: a perspective on the current state, and sampling backwards and forwards

Christian P. Robert, Marcelo Pereyra, Peter J. Green, 2015, 1502.01148.

Exact Monte Carlo likelihood-based inference for jump-diffusion processes

Gareth O. Roberts, Krzysztof G. Latuszy'nski, Fl'avio B. Gonccalves, 2017, Journal of the Royal Statistical Society Series B: Statistical Methodology.