79 citations · 258 across the 61 of their papers we have counts for
10 papers · 1 filter
Multilevel Dimension-Independent Likelihood-Informed MCMC for Large-Scale Inverse Problems
Tiangang Cui, Gianluca Detommaso, Robert Scheichl
We present a non-trivial integration of dimension-independent likelihood-informed (DILI) MCMC (Cui, Law, Marzouk, 2016) and the multilevel MCMC (Dodwell et al., 2015) to explore th…
Multilevel Monte Carlo Simulations of Composite Structures with Uncertain Manufacturing Defects
T. J. Dodwell, S. Kinston, R. Butler +3
By adopting a Multilevel Monte Carlo (MLMC) framework, we show that only a handful of costly fine scale computations are needed to accurately estimate statistics of the failure of…
Correction of coarse-graining errors by a two-level method: application to the Asakura-Oosawa model
Hideki Kobayashi, Paul B. Rohrbach, Robert Scheichl +2
We present a method that exploits self-consistent simulation of coarse-grained and fine-grained models, in order to analyse properties of physical systems. The method uses the coar…
A High-Performance Implementation of a Robust Preconditioner for Heterogeneous Problems
Linus Seelinger, Anne Reinarz, Robert Scheichl
We present an efficient implementation of the highly robust and scalable GenEO preconditioner in the high-performance PDE framework DUNE. The GenEO coarse space is constructed by c…
Unified Analysis of Periodization-Based Sampling Methods for Matérn Covariances
Markus Bachmayr, Ivan G. Graham, Van Kien Nguyen +1
The periodization of a stationary Gaussian random field on a sufficiently large torus comprising the spatial domain of interest is the basis of various efficient computational meth…
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference
Jakob Kruse, Gianluca Detommaso, Ullrich Köthe +1
Many recent invertible neural architectures are based on coupling block designs where variables are divided in two subsets which serve as inputs of an easily invertible (usually af…