Elmar Zander
Cited by
Cited by
Adaptive stochastic galerkin fem
M Eigel, CJ Gittelson, C Schwab, E Zander
Computer Methods in Applied Mechanics and Engineering 270, 247-269, 2014
Solving stochastic systems with low-rank tensor compression
HG Matthies, E Zander
Linear Algebra and its Applications 436 (10), 3819-3838, 2012
Inverse problems in a Bayesian setting
HG Matthies, E Zander, BV Rosić, A Litvinenko, O Pajonk
Computational Methods for Solids and Fluids: Multiscale Analysis …, 2016
Efficient analysis of high dimensional data in tensor formats
M Espig, W Hackbusch, A Litvinenko, HG Matthies, E Zander
Sparse grids and applications, 31-56, 2013
A convergent adaptive stochastic Galerkin finite element method with quasi-optimal spatial meshes
M Eigel, CJ Gittelson, C Schwab, E Zander
ESAIM: Mathematical Modelling and Numerical Analysis 49 (5), 1367-1398, 2015
Parameter estimation via conditional expectation: a Bayesian inversion
HG Matthies, E Zander, BV Rosić, A Litvinenko
Advanced modeling and simulation in engineering sciences 3, 1-21, 2016
Parametric and uncertainty computations with tensor product representations
HG Matthies, A Litvinenko, O Pajonk, BV Rosić, E Zander
Uncertainty Quantification in Scientific Computing: 10th IFIP WG 2.5 Working …, 2012
Alea-a python framework for spectral methods and low-rank approximations in uncertainty quantification
M Eigel, E Zander
Low rank surrogates for polymorphic fields 33, 2020
Bayesian parameter estimation via filtering and functional approximations
HG Matthies, A Litvinenko, BV Rosic, E Zander
arXiv preprint arXiv:1611.09293, 2016
Tensor approximation methods for stochastic problems
EK Zander
Dissertation, Braunschweig, Technische Universität Braunschweig, 2012, 2013
Iterative algorithms for the post-processing of high-dimensional data
M Espig, W Hackbusch, A Litvinenko, HG Matthies, E Zander
Journal of Computational Physics 410, 109396, 2020
Tensor product methods for stochastic problems
E Zander, HG Matthies
PAMM: Proceedings in Applied Mathematics and Mechanics 7 (1), 2040067-2040068, 2007
Post-processing of high-dimensional data
M Espig, W Hackbusch, A Litvinenko, HG Matthies, E Zander
arXiv preprint arXiv:1906.05669, 2019
Sparse representations in stochastic mechanics
HG Matthies, E Zander
Computational Methods in Stochastic Dynamics, 247-265, 2010
Stochastic galerkin library
E Zander
Technische Universität Braunschweig, 2008
A worked-out example of surrogate-based bayesian parameter and field identification methods
N Friedman, C Zoccarato, E Zander, HG Matthies
Bayesian Methods for the Analysis of Engineering Systems; Chiachio Ruano, J …, 2021
Calibration of an extended eddy viscosity turbulence model using uncertainty quantification
G Subbian, AC Botelho e Souza, R Radespiel, E Zander, N Friedman, ...
AIAA Scitech 2020 Forum, 1031, 2020
Bayesian calibration of model coefficients for a simulation of flow over porous material involving SVM classification
N Friedman, P Kumar, E Zander, HG Matthies
PAMM 16 (1), 669-670, 2016
Bayesian calibration of volume averaged RANS model parameters for turbulent flow simulations over porous materials
P Kumar, N Friedman, E Zander, R Radespiel
New Results in Numerical and Experimental Fluid Mechanics XI: Contributions …, 2018
Inverse problems in a Bayesian setting, Computational Methods for Solids and Fluids Multiscale Analysis, Probability Aspects and Model Reduction Editors: Ibrahimbegovic, Adnan …
H Matthies, E Zander, O Pajonk, B Rosic, A Litvinenko
Springer, 2016
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