Auflistung nach Autor "Eberle, Andreas"
Anzeige der Dokumente 1-7 von 7
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Convergence of McKean-Vlasov processes and Markov Chain Monte Carlo methods for mean-field models
(2022-10-11)In recent years, analysing the long-time behaviour of stochastic processes has received increasing interest. Firstly, efficient sampling of a given probability measure is an important task that arises in various fields ... -
Convergence of Multilevel MCMC methods on path spaces
(2014-07-28)Within this work, the efficiency of Markov Chain Monte Carlo methods on infinite dimensional spaces, such as function spaces, is analyzed. We study two aspects in this respect:<br /> The first aspect is a Multilevel Markov ... -
Couplings and Kantorovich contractions with explicit rates for diffusions
(2017-09-15)We consider certain classes of diffusion and McKean-Vlasov processes and provide non-asymptotic quantifications of the longtime behavior using coupling methods. The thesis is divided into three main parts.<br /> In the ... -
Non-asymptotic Error Bounds for Sequential MCMC Methods
(2012-07-17)Sequential MCMC methods are a class of stochastic numerical integration methods for target measures $\mu$ which cannot feasibly be attacked directly with standard MCMC methods due to the presence of multiple well-separated ... -
On the Feynman-Kac formula for Schrödinger semigroups on vector bundles
(2011-05-11)In this thesis we generalize the Feynman-Kac formula to semigroups that correspond to Schrödinger type operators with possibly singular potentials on vector bundles over noncompact Riemannian manifolds. <br /> This ... -
Shock Fluctuations in KPZ Growth Models
(2015-10-09)The Kardar-Parisi-Zhang (KPZ) universality class is a class of stochastic growth models which has attracted much interest, especially since the discovery about 15 years ago that the Tracy-Widom distributions from random ... -
Stability of Stochastic Differential Equations with Jumps by the Coupling Method
(2017-10-06)The topic of this thesis is the study of R^d-valued stochastic processes defined as solutions to stochastic differential equations (SDEs) driven by a noise with a jump component. Our main focus are SDEs driven by pure jump ...
