research
∙
04/04/2023
Solidarity of Gibbs Samplers: the spectral gap
Gibbs samplers are preeminent Markov chain Monte Carlo algorithms used i...
share
research
∙
06/10/2021
Bayesian inference of a non-local proliferation model
From a systems biology perspective the majority of cancer models, althou...
research
∙
06/09/2021
Convergence of the EBT method for a non-local model of cell proliferation with discontinuous interaction kernel
We consider the EBT algorithm (a particle method) for the non-local equa...
research
∙
06/13/2020
Structure learning for CTBN's via penalized maximum likelihood methods
The continuous-time Bayesian networks (CTBNs) represent a class of stoch...
research
∙
09/14/2019
Adaptive Bayesian SLOPE – High-dimensional Model Selection with Missing Values
The selection of variables with high-dimensional and missing data is a m...
research
∙
03/27/2019
Jaccard/Tanimoto similarity test and estimation methods
Binary data are used in a broad area of biological sciences. Using binar...
research
∙
02/02/2019
Non-asymptotic Analysis of Biased Stochastic Approximation Scheme
Stochastic approximation (SA) is a key method used in statistical learni...
research
∙
08/08/2018
Asymptotics of maximum likelihood estimators based on Markov chain Monte Carlo methods
In many complex statistical models maximum likelihood estimators cannot ...
research
∙
05/04/2018
Analysis of nonsmooth stochastic approximation: the differential inclusion approach
In this paper we address the convergence of stochastic approximation whe...
research
∙
02/26/2018