Blazej Miasojedow
Blazej Miasojedow
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Cited by
Analysis of Langevin Monte Carlo via convex optimization
A Durmus, S Majewski, B Miasojedow
The Journal of Machine Learning Research 20 (1), 2666-2711, 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), 1-11, 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), 3582, 2017
An adaptive parallel tempering algorithm
B Miasojedow, E Moulines, M Vihola
Journal of Computational and Graphical Statistics 22 (3), 649-664, 2013
Non-asymptotic analysis of biased stochastic approximation scheme
B Karimi, B Miasojedow, E Moulines, HT Wai
Conference on Learning Theory, 1944-1974, 2019
Nonasymptotic bounds on the estimation error of MCMC algorithms
K Łatuszyński, B Miasojedow, W Niemiro
Analysis of nonsmooth stochastic approximation: the differential inclusion approach
S Majewski, B Miasojedow, E Moulines
arXiv preprint arXiv:1805.01916, 2018
A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave
J Bracher, D Wolffram, J Deuschel, K Görgen, JL Ketterer, A Ullrich, ...
Nature communications 12 (1), 5173, 2021
Optimal scaling for the transient phase of the random walk Metropolis algorithm: The mean-field limit
B Jourdain, T Leličvre, B Miasojedow
State-dependent swap strategies and automatic reduction of number of temperatures in adaptive parallel tempering algorithm
MK Łącki, B Miasojedow
Statistics and Computing 26, 951-964, 2016
Optimal scaling for the transient phase of Metropolis Hastings algorithms: the longtime behavior
B Jourdain, T Leličvre, B Miasojedow
Hoeffding’s inequalities for geometrically ergodic Markov chains on general state space
B Miasojedow
Statistics & Probability Letters 87, 115-120, 2014
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
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
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
Adaptive Bayesian SLOPE: Model Selection With Incomplete Data
W Jiang, M Bogdan, J Josse, S Majewski, B Miasojedow, V Ročková, ...
Journal of Computational and Graphical Statistics 31 (1), 113-137, 2022
Predicting the redshift of γ-ray-loud agns using supervised machine learning
MG Dainotti, M Bogdan, A Narendra, SJ Gibson, B Miasojedow, I Liodakis, ...
The Astrophysical Journal 920 (2), 118, 2021
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
masstodon: A Tool for Assigning Peaks and Modeling Electron Transfer Reactions in Top-Down Mass Spectrometry
MK Łacki, F Lermyte, B Miasojedow, MP Startek, F Sobott, D Valkenborg, ...
Analytical chemistry 91 (3), 1801-1807, 2019
Geometric ergodicity of Rao and Teh’s algorithm for Markov jump processes and CTBNs
B Miasojedow, W Niemiro
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