2 citations · 2 across the 1 of their papers we have counts for
8 papers
Robust random walk-like Metropolis-Hastings algorithms for concentrating posteriors
Daniel Rudolf, Björn Sprungk
Motivated by Bayesian inference with highly informative data we analyze the performance of random walk-like Metropolis-Hastings algorithms for approximate sampling of increasingly…
Geometric convergence of elliptical slice sampling
Viacheslav Natarovskii, Daniel Rudolf, Björn Sprungk
For Bayesian learning, given likelihood function and Gaussian prior, the elliptical slice sampler, introduced by Murray, Adams and MacKay 2010, provides a tool for the construction…
Stability of doubly-intractable distributions
Michael Habeck, Daniel Rudolf, Björn Sprungk
Doubly-intractable distributions appear naturally as posterior distributions in Bayesian inference frameworks whenever the likelihood contains a normalizing function . Having tw…
On the Local Lipschitz Stability of Bayesian Inverse Problems
Björn Sprungk
In this note we consider the stability of posterior measures occuring in Bayesian inference w.r.t. perturbations of the prior measure and the log-likelihood function. This extends…
On Expansions and Nodes for Sparse Grid Collocation of Lognormal Elliptic PDEs
Oliver G. Ernst, Björn Sprungk, Lorenzo Tamellini
This work is a follow-up to our previous contribution ("Convergence of sparse collocation for functions of countably many Gaussian random variables (with application to elliptic PD…
Quantitative spectral gap estimate and Wasserstein contraction of simple slice sampling
Viacheslav Natarovskii, Daniel Rudolf, Björn Sprungk
We prove Wasserstein contraction of simple slice sampling for approximate sampling w.r.t. distributions with log-concave and rotational invariant Lebesgue densities. This yields, i…