Blazej Miasojedow
Blazej Miasojedow
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Cited by
An adaptive parallel tempering algorithm
B Miasojedow, E Moulines, M Vihola
Journal of Computational and Graphical Statistics 22 (3), 649-664, 2013
Analysis of Langevin Monte Carlo via Convex Optimization.
A Durmus, S Majewski, B Miasojedow
J. Mach. Learn. Res. 20, 73:1-73:46, 2019
Predicting the outcomes of organic reactions via machine learning: are current descriptors sufficient?
G Skoraczyński, P Dittwald, B Miasojedow, S Szymkuć, EP Gajewska, ...
Scientific reports 7 (1), 1-9, 2017
Nonasymptotic bounds on the estimation error of MCMC algorithms
K Łatuszyński, B Miasojedow, W Niemiro
Bernoulli 19 (5A), 2033-2066, 2013
Optimal scaling for the transient phase of the random walk Metropolis algorithm: the mean-field limit
B Jourdain, T Lelievre, B Miasojedow
The Annals of Applied Probability 25 (4), 2263-2300, 2015
Optimal scaling for the transient phase of Metropolis Hastings algorithms: the longtime behavior
B Jourdain, T Lelievre, B Miasojedow
Bernoulli 20 (4), 1930-1978, 2014
Non-asymptotic analysis of biased stochastic approximation scheme
B Karimi, B Miasojedow, É Moulines, HT Wai
arXiv preprint arXiv:1902.00629, 2019
Optimization of mutation pressure in relation to properties of protein-coding sequences in bacterial genomes
P Błażej, B Miasojedow, M Grabińska, P Mackiewicz
PloS one 10 (6), e0130411, 2015
Hoeffding’s inequalities for geometrically ergodic Markov chains on general state space
B Miasojedow
Statistics & Probability Letters 87, 115-120, 2014
Analysis of nonsmooth stochastic approximation: the differential inclusion approach
S Majewski, B Miasojedow, E Moulines
arXiv preprint arXiv:1805.01916, 2018
State-dependent swap strategies and automatic reduction of number of temperatures in adaptive parallel tempering algorithm
MK Łącki, B Miasojedow
Statistics and Computing 26 (5), 951-964, 2016
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
Metropolis-type algorithms for continuous time Bayesian networks
B Miasojedow, W Niemiro, J Noble, K Opalski
arXiv preprint arXiv:1403.4035, 2014
masstodon: A Tool for Assigning Peaks and Modeling Electron Transfer Reactions in Top-Down Mass Spectrometry
MK Łącki, F Lermyte, B Miasojedow, MP Startek, F Sobott, D Valkenborg, ...
Analytical chemistry 91 (3), 1801-1807, 2019
Jaccard/Tanimoto similarity test and estimation methods for biological presence-absence data
NC Chung, BŻ Miasojedow, M Startek, A Gambin
BMC bioinformatics 20 (15), 644, 2019
Sparse estimation in ising model via penalized Monte Carlo methods
B Miasojedow, W Rejchel
The Journal of Machine Learning Research 19 (1), 2979-3004, 2018
Geometric ergodicity of Rao and Teh’s algorithm for Markov jump processes and CTBNs
B Miasojedow, W Niemiro
Electronic Journal of Statistics 11 (2), 4629-4648, 2017
The wasserstein distance as a dissimilarity measure for mass spectra with application to spectral deconvolution
S Majewski, MA Ciach, M Startek, W Niemyska, B Miasojedow, A Gambin
18th International Workshop on Algorithms in Bioinformatics (WABI 2018), 2018
Adaptive Monte Carlo Maximum Likelihood
B Miasojedow, W Niemiro, J Palczewski, W Rejchel
Challenges in Computational Statistics and Data Mining, 247-270, 2016
Particle Gibbs algorithms for Markov jump processes
B Miasojedow, W Niemiro
arXiv preprint arXiv:1505.01434, 2015
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