Krzysztof Latuszynski
TitleCited byYear
Bayesian computation: a summary of the current state, and samples backwards and forwards
PJ Green, K Łatuszyński, M Pereyra, CP Robert
Statistics and Computing 25 (4), 835-862, 2015
1052015
Adaptive Gibbs samplers and related MCMC methods
K Latuszynski, GO Roberts, JS Rosenthal
The Annals of Applied Probability, 2013, 2013
532013
Variance bounding and geometric ergodicity of Markov chain Monte Carlo kernels for approximate Bayesian computation
A Lee, K Latuszynski
Biometrika 101 (3), 655--671, 2014
432014
Nonasymptotic bounds on the estimation error of MCMC algorithms
K Łatuszyński, B Miasojedow, W Niemiro
Bernoulli 19 (5A), 2033-2066, 2013
43*2013
Rigorous confidence bounds for MCMC under a geometric drift condition
K Łatuszyński, W Niemiro
Journal of Complexity 27 (1), 23-38, 2011
35*2011
A few remarks on “Fixed-width output analysis for Markov chain Monte Carlo” by Jones et al
W Bednorz, K Latuszynski
Journal of the American Statistical Association 102 (480), 1485-1486, 2007
302007
A Regeneration Proof of the Central Limit Theorem for Uniformly Ergodic Markov Chains
W Bednorz, K Latuszynski, R Latala
Elect. Comm. in Probab 13, 85-98, 2008
282008
Simulating events of unknown probabilities via reverse time martingales
K Łatuszyński, I Kosmidis, O Papaspiliopoulos, GO Roberts
Random Structures & Algorithms 38 (4), 441-452, 2011
262011
CLTs and asymptotic variance of time-sampled Markov chains
K Łatuszyński, GO Roberts
Methodology and Computing in Applied Probability, 1-11, 2011
142011
Stability of Adversarial Markov Chains, with an Application to Adaptive MCMC Algorithms
RV Craiu, L Gray, K Latuszynski, N Madras, GO Roberts, JS Rosenthal
The Annals of Applied Probability 25 (6), 3592–3623, 2015
112015
Zróżnicowanie wynagrodzeń kobiet i mężczyzn na polskim rynku pracy w 2004 roku,[w:] Wzrost gospodarczy a bezrobocie i nierówności w podziale dochodu, red
K Łatuszyński, ŁP Woźny
W. Pacho, M. Garbicz, Szkoła Główna Handlowa, Warszawa, 2008
10*2008
Individual adaptation: an adaptive MCMC scheme for variable selection problems
J Griffin, K Latuszynski, M Steel
arXiv preprint arXiv:1412.6760, 2014
92014
The containment condition and AdapFail algorithms
K Łatuszyński, JS Rosenthal
Journal of Applied Probability, 2014
82014
Nonasymptotic bounds on the mean square error for MCMC estimates via renewal techniques
K Łatuszyński, B Miasojedow, W Niemiro
Monte Carlo and Quasi-Monte Carlo Methods 2010, 539-555, 2012
82012
Perfect simulation using atomic regeneration with application to Sequential Monte Carlo
A Lee, A Doucet, K Łatuszyński
arXiv preprint arXiv:1407.5770, 2014
72014
Regeneration and fixed-width analysis of Markov Chain Monte Carlo algorithms
K Łatuszyński
PhD Dissertation, 2008. Available at arXiv: 0907.4716 v1, 2008
7*2008
Continious-time importance sampling: Monte carlo methods which avoid time-discretisation error
P Fearnhead, K Latuszynski, GO Roberts, G Sermaidis
arXiv preprint arXiv:1712.06201, 2017
62017
A Framework for Adaptive MCMC Targeting Multimodal Distributions
E Pompe, C Holmes, K Łatuszyński
arXiv preprint arXiv:1812.02609, 2018
5*2018
Exact Monte Carlo likelihood-based inference for jump-diffusion processes
FB Gonçalves, KG Łatuszyński, GO Roberts
arXiv preprint arXiv:1707.00332, 2017
52017
In Search of Lost (Mixing) Time: Adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p
J Griffin, K Latuszynski, M Steel
arXiv preprint arXiv:1708.05678, 2017
52017
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Articles 1–20