The influence of prior knowledge on the expected performance of a classifier. - Vladimir B. Berikov; Alexander Litvinenko (Pattern Recognit. Lett., 2003)

Application of hierarchical matrices for computing the Karhunen-Loève expansion. - Boris N. Khoromskij; Alexander Litvinenko; Hermann G. Matthies (Computing, 2009)

Parametric and Uncertainty Computations with Tensor Product Representations. - Hermann G. Matthies; Alexander Litvinenko; Oliver Pajonk; Bojana V. Rosic; Elmar Zander (WoCoUQ, 2011)

Parameter Identification in a Probabilistic Setting - Bojana V. Rosic; Anna Kucerová; Jan Sykora; Oliver Pajonk; Alexander Litvinenko; Hermann G. Matthies (CoRR, 2012)

Sampling-free linear Bayesian update of polynomial chaos representations. - Bojana V. Rosic; Alexander Litvinenko; Oliver Pajonk; Hermann G. Matthies (J. Comput. Phys., 2012)

Efficient low-rank approximation of the stochastic Galerkin matrix in tensor formats. - Mike Espig; Wolfgang Hackbusch; Alexander Litvinenko; Hermann G. Matthies; Philipp Wähnert (Comput. Math. Appl., 2014)

To Be or Not to Be Intrusive? The Solution of Parametric and Stochastic Equations - the "Plain Vanilla" Galerkin Case. - Loïc Giraldi; Alexander Litvinenko; Dishi Liu; Hermann G. Matthies; Anthony Nouy (SIAM J. Sci. Comput., 2014)

Polynomial Chaos Expansion of Random Coefficients and the Solution of Stochastic Partial Differential Equations in the Tensor Train Format. - Sergey Dolgov; Boris N. Khoromskij; Alexander Litvinenko; Hermann G. Matthies (SIAM/ASA J. Uncertain. Quantification, 2015)

Parameter estimation via conditional expectation: a Bayesian inversion. - Hermann G. Matthies; Elmar Zander; Bojana V. Rosic; Alexander Litvinenko (Adv. Model. Simul. Eng. Sci., 2016)

Quantification of Airfoil Geometry-Induced Aerodynamic Uncertainties - Comparison of Approaches. - Dishi Liu; Alexander Litvinenko; Claudia Schillings; Volker Schulz 001 (SIAM/ASA J. Uncertain. Quantification, 2017)

Tucker Tensor Analysis of Matérn Functions in Spatial Statistics. - Alexander Litvinenko; David E. Keyes; Venera Khoromskaia; Boris N. Khoromskij; Hermann G. Matthies (Comput. Methods Appl. Math., 2019)

Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix Decomposition under Uncertainties. - Vladimir B. Berikov; Alexander Litvinenko (CoRR, 2019)

Solution of the 3D density-driven groundwater flow problem with uncertain porosity and permeability. - Alexander Litvinenko; Dmitriy Logashenko; Raúl Tempone; Gabriel Wittum; David E. Keyes (CoRR, 2019)

Post-Processing of High-Dimensional Data. - Mike Espig; Wolfgang Hackbusch; Alexander Litvinenko; Hermann G. Matthies; Elmar Zander (CoRR, 2019)

Likelihood approximation with hierarchical matrices for large spatial datasets. - Alexander Litvinenko; Ying Sun 002; Marc G. Genton; David E. Keyes (Comput. Stat. Data Anal., 2019)

Iterative algorithms for the post-processing of high-dimensional data. - Mike Espig; Wolfgang Hackbusch; Alexander Litvinenko; Hermann G. Matthies; Elmar Zander (J. Comput. Phys., 2020)

On a Weakly Supervised Classification Problem. - Vladimir B. Berikov; Alexander Litvinenko; Igor Pestunov; Yuriy Sinyavskiy (AIST, 2021)

Weakly Supervised Regression Using Manifold Regularization and Low-Rank Matrix Representation. - Vladimir B. Berikov; Alexander Litvinenko (MOTOR, 2021)

Solving weakly supervised regression problem using low-rank manifold regularization. - Vladimir B. Berikov; Alexander Litvinenko (CoRR, 2021)

Identification of unknown parameters and prediction with hierarchical matrices. - Alexander Litvinenko; Ronald Kriemann; Vladimir B. Berikov (CoRR, 2021)

Computing f-Divergences and Distances of High-Dimensional Probability Density Functions - Low-Rank Tensor Approximations. - Alexander Litvinenko; Youssef M. Marzouk; Hermann G. Matthies; Marco Scavino; Alessio Spantini (CoRR, 2021)

Uncertainty quantification in coastal aquifers using the multilevel Monte Carlo method. - Alexander Litvinenko; Dmitry Logashenko; Raúl Tempone; Ekaterina Vasilyeva; Gabriel Wittum (CoRR, 2023)

Computing f -divergences and distances of high-dimensional probability density functions. - Alexander Litvinenko; Youssef M. Marzouk; Hermann G. Matthies; Marco Scavino; Alessio Spantini (Numer. Linear Algebra Appl., 2023)

Estimation of uncertainties in the density driven flow in fractured porous media using MLMC. - Dmitry Logashenko; Alexander Litvinenko; Raúl Tempone; Gabriel Wittum (CoRR, 2024)

Uncertainty quantification in the Henry problem using the multilevel Monte Carlo method. - Dmitry Logashenko; Alexander Litvinenko; Raúl Tempone; Ekaterina Vasilyeva; Gabriel Wittum (J. Comput. Phys., 2024)