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20152026
most citedCoupling and exponential ergodicity for stochastic differential equations driven by Lévy processes

40 citations · 69 across the 16 of their papers we have counts for

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Showing 2018Show all

2 papers · 1 filter

math.PR2018

Quantitative contraction rates for Markov chains on general state spaces

Andreas Eberle, Mateusz B. Majka

We investigate the problem of quantifying contraction coefficients of Markov transition kernels in Kantorovich ( Wasserstein) distances. For diffusion processes, relatively pr…

math.PR2018

Non-asymptotic bounds for sampling algorithms without log-concavity

Mateusz B. Majka, Aleksandar Mijatović, Lukasz Szpruch

Discrete time analogues of ergodic stochastic differential equations (SDEs) are one of the most popular and flexible tools for sampling high-dimensional probability measures. Non-a…