Dr. Alexander Litvinenko
Rheinisch Westfalische Technische Hochschule Aachen
Other, Mathematics
Germany
My co-authors include
Venera Khoromskaia
Orken Mamyrbayev
Find me at
My Publications
How to speed up typical statistical tasks in high-dimensions and for large data sets
Computational Methods in Applied Mathematics
July 2018
How to speed up typical linear algebra tasks in spatio-temporal statistics? Especially if there are a lot of data and these data are high dimensional. During last yeas quite a lot was done in the ...
Low-rank tensor methods to solve PDEs with uncertain coefficients
SIAM/ASA Journal on Uncertainty Quantification
January 2015
We apply the tensor train technique to solve elliptic PDE with uncertain coefficients. After discretisation stochastic variables the problem dimension becomes very high (10-300). How to work in suc...
Analysis and estimation of tensor ranks of the stochastic Galerkin matrix
Computers & Mathematics with Applications
March 2014
We consider an elliptic PDE with uncertain diffusion coefficient. This is a highly - dimensional problem, and usual methods either do not work or very slow. To solve it we compute a tensor approxim...
Does stochastic Galerkin method requires modifications in the existing deterministic G...
SIAM Journal on Scientific Computing
January 2014
There are intrusive and non-intrusive methods to quantify uncertainty or to solve a stochastic PDE. Intrusive *means* that we need to modify the existing deterministic solver, and non-intrusive - d...
How we can massively speedup statistical interpolation (Kriging)
Mathematical Geosciences
April 2013
Assume we have some observations and we would like to interpolate these data onto new locations. A typical example is: weather stations in Germany measure weather only locally around these station...
How to approximate covariance matrices and Karhunen-Loeve expansion with a linear compl...
Computing
October 2008
We applied hierarchical (H-) matrices [Hackbusch 99] for approximating covariance matrices and computing Karhunen-Loeve expansion. The H-matrix techniques allows us to do it with O(n log n) computa...
Computing f‐divergences and distances of high‐dimensional probability density functions
Numerical Linear Algebra with Applications
September 2022
On a Weakly Supervised Classification Problem
January 2022
MLMC method to estimate propagation of uncertainties in electromagnetic fields scattere...
PAMM
January 2021
Weakly Supervised Regression Using Manifold Regularization and Low-Rank Matrix Represen...
January 2021
How to quantify uncertainties in the Elder-like problem
GEM - International Journal on Geomathematics
March 2020
How to compute level sets, histograms, maxima, minima in a very large data set?
Journal of Computational Physics
March 2020
GENERATIONS IN BAYESIAN NETWORKS
Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska
September 2019
Cheap approximation of large unstructured dense covariance matrices
Computational Statistics & Data Analysis
September 2019
We apply parallel hierarchical matrix technique to identify unknown parameters and do...
MethodsX
July 2019
Application of bayesian networks for estimation of individual psychological characteris...
PRZEGLĄD ELEKTROTECHNICZNY
May 2019
Computation of uncertain electromagnetic fields scattered from randomly perturbed objects
IEEE Journal on Multiscale and Multiphysics Computational Techniques
January 2019
New multi-linear algebra algorithms for analysis of large and high-dimensional data sets
January 2019
Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix
January 2019
Comparing theory based and higher-order reduced models for fusion simulation data
Big Data & Information Analytics
January 2018
Propagation of uncertainties in the geometry of airfoil profile into lift and drag
SIAM/ASA Journal on Uncertainty Quantification
January 2017
Advanced linear algebra to generate random fields
PAMM
October 2016
We solve a parameter estimation problem by computing the conditional expectation
Advanced Modeling and Simulation in Engineering Sciences
August 2016
Solving inverse problems with Bayesian approach
January 2016
Parameter identification in a probabilistic setting
Engineering Structures
May 2013
Sampling from the low-cost surrogate model
January 2013
Bayesian Update of PCE coefficients
Journal of Computational Physics
July 2012
A deterministic filter for non-Gaussian Bayesian estimation— Applications to dynamical ...
Physica D Nonlinear Phenomena
April 2012
Parametric and Uncertainty Computations with Tensor Product Representations
January 2012
Data Sparse Computation of the Karhunen‐Loève Expansion
January 2008
Domain Decomposition Based H-Matrix Preconditioners for the Skin Problem
January 2008
Expert knowledge about classes increase the quality of the classifier
Pattern Recognition Letters
November 2003