10 citations · 20 across the 7 of their papers we have counts for
8 papers
A Dynamical Low-rank Multilevel Monte Carlo Estimator for High-Dimensional Kinetic Equations
Chinmay Patwardhan, Sebastian Krumscheid, Jonas Kusch +2
Kinetic equations are used to model a wide range of phenomena important for real-world applications. Their applications span astrophysics, nuclear physics, engineering, and social…
regTPS-KLE: A Novel Approach To Approximate A Gaussian Random Field for Bayesian Spatial Modeling
Joaquin Cavieres, Sebastian Krumscheid
Gaussian random field is a ubiquitous model for spatial phenomena in diverse scientific disciplines. Its approximation is often crucial for computational feasibility in simulation,…
An Investigation into the Distribution of Ratios of Particle Solver-based Likelihoods
Emil Løvbak, Sebastian Krumscheid
We investigate the use of the Metropolis-Hastings algorithm to sample posterior distribution in a Bayesian inverse problem, where the likelihood function is random. Concretely, we…
Low-rank variance reduction for uncertain radiative transfer with control variates
Chinmay Patwardhan, Pia Stammer, Emil Løvbak +2
The radiative transfer equation models various physical processes ranging from plasma simulations to radiation therapy. In practice, these phenomena are often subject to uncertaint…
Reliable Uncertainty Quantification for Fiber Orientation in Composite Molding Processes using Multilevel Polynomial Surrogates
Stjepan Salatovic, Sebastian Krumscheid, Florian Wittemann +1
Fiber orientation is decisive for the mechanical performance of composite materials. During manufacturing, variations in material and process parameters can influence fiber orienta…
A Fully Parallelized and Budgeted Multi-Level Monte Carlo Method and the Application to Acoustic Waves
Niklas Baumgarten, Sebastian Krumscheid, Christian Wieners
We present a novel variant of the multi-level Monte Carlo method that effectively utilizes a reserved computational budget on a high-performance computing system to minimize the me…
Quantifying uncertain system outputs via the multi-level Monte Carlo method -- distribution and robustness measures
Quentin Ayoul-Guilmard, Sundar Ganesh, Sebastian Krumscheid +1
In this work, we consider the problem of estimating the probability distribution, the quantile or the conditional expectation above the quantile, the so called conditional-value-at…
Central limit theorems for multilevel Monte Carlo methods
Håkon Hoel, Sebastian Krumscheid
In this work, we show that uniform integrability is not a necessary condition for central limit theorems (CLT) to hold for normalized multilevel Monte Carlo (MLMC) estimators and w…