Lars Grasedyck

According to our database, Lars Grasedyck authored at least 41 papers between 2003 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Taming numerical imprecision by adapting the KL divergence to negative probabilities.

Simon Pfahler, Peter Georg, Rudolf Schill, Maren Klever, Lars Grasedyck, Rainer Spang, Tilo Wettig

Stat. Comput., October, 2024

Correcting for Observation Bias in Cancer Progression Modeling.

Rudolf Schill, Maren Klever, Andreas Lösch, Y. Linda Hu, Stefan Vocht, Kevin Rupp, Lars Grasedyck, Rainer Spang, Niko Beerenwinkel

J. Comput. Biol., 2024

Overcoming Observation Bias for Cancer Progression Modeling.

Rudolf Schill, Maren Klever, Andreas Lösch, Y. Linda Hu, Stefan Vocht, Kevin Rupp, Lars Grasedyck, Rainer Spang, Niko Beerenwinkel

Proceedings of the Research in Computational Molecular Biology, 2024

2022

Rank Bounds for Approximating Gaussian Densities in the Tensor-Train Format.

Paul B. Rohrbach, Sergey Dolgov, Lars Grasedyck, Robert Scheichl

SIAM/ASA J. Uncertain. Quantification, March, 2022

2021

Differentiated uniformization: A new method for inferring Markov chains on combinatorial state spaces including stochastic epidemic models.

Kevin Rupp, Rudolf Schill, Jonas Süskind, Peter Georg, Maren Klever, Andreas Lösch, Lars Grasedyck, Tilo Wettig, Rainer Spang

CoRR, 2021

2020

Bayesian inversion for electromyography using low-rank tensor formats.

Anna Rörich, Tim A. Werthmann, Dominik Göddeke, Lars Grasedyck

CoRR, 2020

A parameter-dependent smoother for the multigrid method.

Lars Grasedyck, Maren Klever, Christian Löbbert, Tim A. Werthmann

CoRR, 2020

Low-rank tensor methods for Markov chains with applications to tumor progression models.

Peter Georg, Lars Grasedyck, Maren Klever, Rudolf Schill, Rainer Spang, Tilo Wettig

CoRR, 2020

2019

Stable ALS approximation in the TT-format for rank-adaptive tensor completion.

Lars Grasedyck, Sebastian Krämer

Numerische Mathematik, 2019

The multipole approach for EEG forward modeling using the finite element method.

Johannes Vorwerk, Anne Hanrath, Carsten H. Wolters, Lars Grasedyck

NeuroImage, 2019

Finding entries of maximum absolute value in low-rank tensors.

Lars Grasedyck, Lukas Juschka, Christian Löbbert

CoRR, 2019

2018

Distributed hierarchical SVD in the Hierarchical Tucker format.

Lars Grasedyck, Christian Löbbert

Numer. Linear Algebra Appl., 2018

7th Workshop on Matrix Equations and Tensor Techniques.

Peter Benner, Heike Faßbender, Lars Grasedyck, Daniel Kressner, Beatrice Meini, Valeria Simoncini

Numer. Linear Algebra Appl., 2018

2016

Space and Time Parallel Multigrid for Optimization and Uncertainty Quantification in PDE Simulations.

Lars Grasedyck, Christian Löbbert, Gabriel Wittum, Arne Nägel, Volker Schulz, Martin Siebenborn, Rolf Krause, Pietro Benedusi, Uwe Küster, Björn Dick

Proceedings of the Software for Exascale Computing - SPPEXA 2013-2015, 2016

A nearly optimal multigrid method for general unstructured grids.

Lars Grasedyck, Lu Wang, Jinchao Xu

Numerische Mathematik, 2016

Tensor-Sparsity of Solutions to High-Dimensional Elliptic Partial Differential Equations.

Wolfgang Dahmen, Ronald A. DeVore, Lars Grasedyck, Endre Süli

Found. Comput. Math., 2016

2015

Variants of Alternating Least Squares Tensor Completion in the Tensor Train Format.

Lars Grasedyck, Melanie Kluge, Sebastian Krämer

SIAM J. Sci. Comput., 2015

Hierarchical Tensor Approximation of Output Quantities of Parameter-Dependent PDEs.

Jonas Ballani, Lars Grasedyck

SIAM/ASA J. Uncertain. Quantification, 2015

Parallel tensor sampling in the hierarchical Tucker format.

Lars Grasedyck, Ronald Kriemann, Christian Löbbert, Arne Nägel, Gabriel Wittum, Konstantinos Xylouris

Comput. Vis. Sci., 2015

2014

Tree Adaptive Approximation in the Hierarchical Tensor Format.

Jonas Ballani, Lars Grasedyck

SIAM J. Sci. Comput., 2014

2013

A projection method to solve linear systems in tensor format.

Jonas Ballani, Lars Grasedyck

Numer. Linear Algebra Appl., 2013

Solving an elliptic PDE eigenvalue problem via automated multi-level substructuring and hierarchical matrices.

Peter Gerds, Lars Grasedyck

Comput. Vis. Sci., 2013

2012

The AL Basis for the Solution of Elliptic Problems in Heterogeneous Media.

Lars Grasedyck, Isabelle Greff, Stefan A. Sauter

Multiscale Model. Simul., 2012

2011

An Introduction to Hierarchical (H-) Rank and TT-Rank of Tensors with Examples.

Lars Grasedyck, Wolfgang Hackbusch

Comput. Methods Appl. Math., 2011

2010

Hierarchical Singular Value Decomposition of Tensors.

Lars Grasedyck

SIAM J. Matrix Anal. Appl., 2010

2009

Domain decomposition based ℋ-LU preconditioning.

Lars Grasedyck, Ronald Kriemann, Sabine Le Borne

Numerische Mathematik, 2009

A full subtraction approach for finite element method based source analysis using constrained Delaunay tetrahedralisation.

Florian Drechsler, Carsten H. Wolters, Thomas Dierkes, Hang Si, Lars Grasedyck

NeuroImage, 2009

2008

Nonlinear multigrid for the solution of large-scale Riccati equations in low-rank and ℋ-matrix format.

Lars Grasedyck

Numer. Linear Algebra Appl., 2008

2007

Numerical Mathematics of the Subtraction Method for the Modeling of a Current Dipole in EEG Source Reconstruction Using Finite Element Head Models.

Carsten H. Wolters, Harald Köstler, Christian Möller, Jochen Härdtlein, Lars Grasedyck, Wolfgang Hackbusch

SIAM J. Sci. Comput., 2007

Optimal Panel-Clustering in the Presence of Anisotropic Mesh Refinement.

Ivan G. Graham, Lars Grasedyck, Wolfgang Hackbusch, Stefan A. Sauter

SIAM J. Numer. Anal., 2007

A Multigrid Method to Solve Large Scale Sylvester Equations.

Lars Grasedyck, Wolfgang Hackbusch

SIAM J. Matrix Anal. Appl., 2007

A structured low-rank wavelet solver for the Ornstein-Zernike integral equation.

Maxim V. Fedorov, Heinz-Jürgen Flad, Gennady N. Chuev, Lars Grasedyck, Boris N. Khoromskij

Computing, 2007

2006

H-matrix Preconditioners in Convection-Dominated Problems.

Sabine Le Borne, Lars Grasedyck

SIAM J. Matrix Anal. Appl., 2006

2005

Hybrid cross approximation of integral operators.

Steffen Börm, Lars Grasedyck

Numerische Mathematik, 2005

Adaptive Recompression of <i>H</i> -Matrices for BEM.

Lars Grasedyck

Computing, 2005

2004

Existence of a low rank or ℋ-matrix approximant to the solution of a Sylvester equation.

Lars Grasedyck

Numer. Linear Algebra Appl., 2004

Adaptive Geometrically Balanced Clustering of H-Matrices.

Lars Grasedyck, Wolfgang Hackbusch, Sabine Le Borne

Computing, 2004

Existence and Computation of Low Kronecker-Rank Approximations for Large Linear Systems of Tensor Product Structure.

Lars Grasedyck

Computing, 2004

Low-Rank Approximation of Integral Operators by Interpolation.

Steffen Börm, Lars Grasedyck

Computing, 2004

2003

Solution of Large Scale Algebraic Matrix Riccati Equations by Use of Hierarchical Matrices.

Lars Grasedyck, Wolfgang Hackbusch, Boris N. Khoromskij

Computing, 2003

Construction and Arithmetics of H-Matrices.

Lars Grasedyck, Wolfgang Hackbusch

Computing, 2003