Alexander Litvinenko

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Hermann G MatthiesProfessor of Computer Science, Inst. of Scientific Computing, TU BraunschweigVerified email at tu-bs.de
Oliver PajonkElektrobit Automotive GmbHVerified email at pjnk.de
Elmar ZanderTechnische Universität BraunschweigVerified email at tu-bs.de
Boris KhoromskijSenior Researcher, Max-Planck Institute for Mathematics in the Sciences, LeipzigVerified email at mis.mpg.de
Raul TemponeProfessor of Applied Mathematics, Alexander von Humboldt Professor RWTH-Aachen & KAUSTVerified email at kaust.edu.sa
Ying SunAssociate Professor of Statistics, King Abdullah University of Science and Technology (KAUST)Verified email at kaust.edu.sa
Marc G GentonAl-Khawarizmi Distinguished Professor of Statistics, KAUSTVerified email at kaust.edu.sa
Sergey DolgovUniversity of BathVerified email at bath.ac.uk
Jan SýkoraAssistant professor, CTU in Prague, FCE, Dept. of MechanicsVerified email at fsv.cvut.cz
Anna KučerováAssociate Professor, Czech Technical University in PragueVerified email at cvut.cz
Hakan BagciKing Abdullah University of Science and Technology (KAUST)Verified email at kaust.edu.sa
Wolfgang NowakStochastic Modelling of Hydrosystems, Universität StuttgartVerified email at iws.uni-stuttgart.de
Volker SchulzUniversity of TrierVerified email at uni-trier.de
Anthony NOUYProfessor of Mathematics, Nantes Université, Ecole Centrale de NantesVerified email at ec-nantes.fr
Loïc GiraldiResearch ScientistVerified email at cea.fr
Tarek MoselhyMassachusetts Institute of TechnologyVerified email at mit.edu
Hatem LtaiefPrincipal Research Scientist, KAUSTVerified email at kaust.edu.sa
Ahmad AbdelfattahResearch Assistant Professor, Innovative Computing Laboratory, University of TennesseeVerified email at icl.utk.edu
Hüseyin Arda ÜlküYeditepe UniversityVerified email at yeditepe.edu.tr
Abdul-Lateef Haji-AliHeriot-Watt UniversityVerified email at hw.ac.uk

Alexander Litvinenko

Chair of Mathematics for Uncertainty Quantification, RWTH Aachen

Verified email at uq.rwth-aachen.de - Homepage

Uncertainty quantification hierarchical matrices low-rank tensor methods domain decomposition


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Parameter identification in a probabilistic setting BV Rosić, A Kučerová, J Sýkora, O Pajonk, A Litvinenko, HG Matthies Engineering Structures 50, 179-196, 2013	126	2013
Application of hierarchical matrices for computing the Karhunen–Loève expansion BN Khoromskij, A Litvinenko, HG Matthies Computing 84 (1), 49-67, 2009	119	2009
Sampling-free linear Bayesian update of polynomial chaos representations BV Rosić, A Litvinenko, O Pajonk, HG Matthies Journal of Computational Physics 231 (17), 5761-5787, 2012	93	2012
Polynomial Chaos Expansion of Random Coefficients and the Solution of Stochastic Partial Differential Equations in the Tensor Train Format S Dolgov, BN Khoromskij, A Litvinenko, HG Matthies IAM/ASA J. Uncertainty Quantification 3 (1), 1109-1135, 2015	88	2015
Efficient low-rank approximation of the stochastic Galerkin matrix in tensor formats M Espig, W Hackbusch, A Litvinenko, HG Matthies, P Wähnert Computers & Mathematics with Applications 67 (4), 818-829, 2014	86	2014
A deterministic filter for non-Gaussian Bayesian estimation—applications to dynamical system estimation with noisy measurements O Pajonk, BV Rosić, A Litvinenko, HG Matthies Physica D: Nonlinear Phenomena 241 (7), 775-788, 2012	84	2012
Inverse Problems in a Bayesian Setting Hermann G. Matthies, Elmar Zander, Oliver Pajonk, Bojana V Rosić, Alexander ... Computational Methods for Solids and Fluids Multiscale Analysis, Probability …, 2016	80*	2016
Likelihood approximation with hierarchical matrices for large spatial datasets A Litvinenko, Y Sun, MG Genton, DE Keyes Computational Statistics & Data Analysis 137, 115-132, 2019	79	2019
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	76	2013
To be or not to be intrusive? The solution of parametric and stochastic equations---the “plain vanilla” Galerkin case L Giraldi, A Litvinenko, D Liu, HG Matthies, A Nouy SIAM Journal on Scientific Computing 36 (6), A2720-A2744, 2014	69	2014
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	62	2016
Kriging and spatial design accelerated by orders of magnitude: Combining low-rank covariance approximations with FFT-techniques W Nowak, A Litvinenko Mathematical Geosciences 45 (4), 411-435, 2013	56	2013
Quantification of airfoil geometry-induced aerodynamic uncertainties---comparison of approaches D Liu, A Litvinenko, C Schillings, V Schulz SIAM/ASA Journal on Uncertainty Quantification 5 (1), 334-352, 2017	47	2017
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	43	2012
Computation of the response surface in the tensor train data format S Dolgov, BN Khoromskij, A Litvinenko, HG Matthies arXiv preprint arXiv:1406.2816, 2014	42	2014
Methods for statistical data analysis with decision trees V Berikov, A Litvinenko Novosibirsk, Sobolev Institute of Mathematics, 2003	40	2003
HLIBCov: Parallel hierarchical matrix approximation of large covariance matrices and likelihoods with applications in parameter identification A Litvinenko, R Kriemann, MG Genton, Y Sun, DE Keyes MethodsX 7, 100600, 2020	29	2020
Sampling and low-rank tensor approximation of the response surface A Litvinenko, HG Matthies, TA El-Moselhy Monte Carlo and Quasi-Monte Carlo Methods 2012, 535-551, 2013	28	2013
Inverse problems and uncertainty quantification A Litvinenko, HG Matthies arXiv preprint arXiv:1312.5048, 2013	27	2013
Tucker tensor analysis of Matérn functions in spatial statistics A Litvinenko, D Keyes, V Khoromskaia, BN Khoromskij, HG Matthies Computational Methods in Applied Mathematics 19 (1), 101-122, 2019	26	2019

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