activity
20172022
most citedMultilevel preconditioner of Polynomial Chaos Method for quantifying uncertainties in a blood pump

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV2022

Using the Order of Tomographic Slices as a Prior for Neural Networks Pre-Training

Yaroslav Zharov, Alexey Ershov, Tilo Baumbach +1

The technical advances in Computed Tomography (CT) allow to obtain immense amounts of 3D data. For such datasets it is very costly and time-consuming to obtain the accurate 3D segm…

stat.AP2021

Hierarchical surrogate-based Approximate Bayesian Computation for an electric motor test bench

David N. John, Livia Stohrer, Claudia Schillings +2

Inferring parameter distributions of complex industrial systems from noisy time series data requires methods to deal with the uncertainty of the underlying data and the used simula…

cs.DC2020

A Simple Model for Portable and Fast Prediction of Execution Time and Power Consumption of GPU Kernels

Lorenz Braun, Sotirios Nikas, Chen Song +2

Characterizing compute kernel execution behavior on GPUs for efficient task scheduling is a non-trivial task. We address this with a simple model enabling portable and fast predict…

physics.flu-dyn2018

Dielectrophoretic force-driven convection in annular geometry under Earth's gravity

Torsten Seelig, Antoine Meyer, Philipp Gerstner +5

Context: A radial temperature gradient together with an inhomogeneous radial electric field gradient is applied to a dielectric fluid confined in a vertical cylindrical annulus ind…

physics.flu-dyn20171 cited

Multilevel preconditioner of Polynomial Chaos Method for quantifying uncertainties in a blood pump

Chen Song, Vincent Heuveline

More than 23 million people are suffered by Heart failure worldwide. Despite the modern transplant operation is well established, the lack of heart donations becomes a big restrict…