488 citations · 3k across the 119 of their papers we have counts for
37 papers · 1 filter
Rates of convergence for density estimation with generative adversarial networks
Nikita Puchkin, Sergey Samsonov, Denis Belomestny +2
In this work we undertake a thorough study of the non-asymptotic properties of the vanilla generative adversarial networks (GANs). We prove an oracle inequality for the Jensen-Shan…
Variance reduction for dependent sequences with applications to Stochastic Gradient MCMC
D. Belomestny, L. Iosipoi, E. Moulines +2
In this paper we propose a novel and practical variance reduction approach for additive functionals of dependent sequences. Our approach combines the use of control variates with t…
Variance reduction for Markov chains with application to MCMC
D. Belomestny, L. Iosipoi, E. Moulines +2
In this paper we propose a novel variance reduction approach for additive functionals of Markov chains based on minimization of an estimate for the asymptotic variance of these fun…
A quantitative Mc Diarmid's inequality for geometrically ergodic Markov chains
Antoine Havet, Matthieu Lerasle, Eric Moulines +1
We state and prove a quantitative version of the bounded difference inequality for geometrically ergodic Markov chains. Our proof uses the same martingale decomposition as \cite{MR…
On the two-filter approximations of marginal smoothing distributions in general state space models
Thi Ngoc Minh Nguyen, Sylvain Le Corff, Eric Moulines
A prevalent problem in general state space models is the approximation of the smoothing distribution of a state conditional on the observations from the past, the present, and the…
High-dimensional Bayesian inference via the Unadjusted Langevin Algorithm
Alain Durmus, Eric Moulines
We consider in this paper the problem of sampling a high-dimensional probability distribution having a density with respect to the Lebesgue measure on , known up…