All Stories

  1. Density-driven flow problem with fractures: testing multilevel Monte Carlo and multigrid methods

    Article • Engineering With Computers, December 2024, Springer Science + Business Media

    Dr. Alexander Litvinenko

  2. Solving the Henry saltwater problem by Multi-level Monte Carlo and multigrid methods

    Article • Journal of Computational Physics, February 2024, Elsevier

    Dr. Alexander Litvinenko

  3. Modeling of salinisation of coastal aquifers

    Article • PAMM, September 2023, Wiley

    Dr. Alexander Litvinenko

  4. Weakly supervised multi-target regression problem with uncertain labels

    Article • January 2023, Springer Science + Business Media

    Dr. Alexander Litvinenko

  5. How to compute the Kullback–Leibler divergence if probability density function is unknown?

    Article • Numerical Linear Algebra with Applications, September 2022, Wiley

    Dr. Alexander Litvinenko

  6. Supervised classification when there is uncertainty about a part of the data

    Article • January 2022, Springer Science + Business Media

    Dr. Alexander Litvinenko

  7. MLMC method to estimate propagation of uncertainties in electromagnetic fields scattered from objects of uncertain shapes

    Article • PAMM, January 2021, Wiley

    Dr. Alexander Litvinenko

  8. How to speed up the weakly supervised regression

    Article • January 2021, Springer Science + Business Media

    Dr. Alexander Litvinenko

  9. How to quantify uncertainties in the Elder-like problem

    Article • GEM - International Journal on Geomathematics, March 2020, Springer Science + Business Media

    Dr. Alexander Litvinenko

  10. How to compute level sets, histograms, maxima, minima in a very large data set?

    Article • Journal of Computational Physics, March 2020, Elsevier

    Dr. Alexander Litvinenko

  11. GENERATIONS IN BAYESIAN NETWORKS

    Article • Informatyka Automatyka Pomiary w Gospodarce i Ochronie Środowiska, September 2019, Politechnika Lubelska

    Dr. Alexander Litvinenko, Orken Mamyrbayev

  12. Cheap approximation of large unstructured dense covariance matrices

    Article • Computational Statistics & Data Analysis, September 2019, Elsevier

    Dr. Alexander Litvinenko

  13. We apply parallel hierarchical matrix technique to identify unknown parameters and do predictions

    Article • MethodsX, July 2019, Elsevier

    Dr. Alexander Litvinenko

  14. Application of bayesian networks for estimation of individual psychological characteristics

    Article • PRZEGLĄD ELEKTROTECHNICZNY, May 2019, Wydawnictwo SIGMA-NOT, sp. z.o.o.

    Dr. Alexander Litvinenko, Orken Mamyrbayev

  15. Computation of uncertain electromagnetic fields scattered from randomly perturbed objects

    Article • IEEE Journal on Multiscale and Multiphysics Computational Techniques, January 2019, Institute of Electrical & Electronics Engineers (IEEE)

    Dr. Alexander Litvinenko

  16. New multi-linear algebra algorithms for analysis of large and high-dimensional data sets

    Article • January 2019, ECCOMAS

    Dr. Alexander Litvinenko

  17. Semi-Supervised Regression using Cluster Ensemble and Low-Rank Co-Association Matrix

    Article • January 2019, ECCOMAS

    Dr. Alexander Litvinenko

  18. How to speed up typical statistical tasks in high-dimensions and for large data sets

    Article • Computational Methods in Applied Mathematics, July 2018, De Gruyter

    Venera Khoromskaia, Dr. Alexander Litvinenko

  19. Comparing theory based and higher-order reduced models for fusion simulation data

    Article • Big Data & Information Analytics, January 2018, American Institute of Mathematical Sciences (AIMS)

    Dr. Alexander Litvinenko

  20. Propagation of uncertainties in the geometry of airfoil profile into lift and drag

    Article • SIAM/ASA Journal on Uncertainty Quantification, January 2017, Society for Industrial & Applied Mathematics (SIAM)

    Dr. Alexander Litvinenko

  21. Advanced linear algebra to generate random fields

    Article • PAMM, October 2016, Wiley

    Dr. Alexander Litvinenko

  22. We solve a parameter estimation problem by computing the conditional expectation

    Article • Advanced Modeling and Simulation in Engineering Sciences, August 2016, Springer Science + Business Media

    Dr. Alexander Litvinenko

  23. Solving inverse problems with Bayesian approach

    Article • January 2016, Springer Science + Business Media

    Dr. Alexander Litvinenko

  24. Low-rank tensor methods to solve PDEs with uncertain coefficients

    Article • SIAM/ASA Journal on Uncertainty Quantification, January 2015, Society for Industrial & Applied Mathematics (SIAM)

    Dr. Alexander Litvinenko

  25. Analysis and estimation of tensor ranks of the stochastic Galerkin matrix

    Article • Computers & Mathematics with Applications, March 2014, Elsevier

    Dr. Alexander Litvinenko

  26. Does stochastic Galerkin method requires modifications in the existing deterministic Galerkin code?

    Article • SIAM Journal on Scientific Computing, January 2014, Society for Industrial & Applied Mathematics (SIAM)

    Dr. Alexander Litvinenko

  27. Parameter identification in a probabilistic setting

    Article • Engineering Structures, May 2013, Elsevier

    Dr. Alexander Litvinenko

  28. How we can massively speedup statistical interpolation (Kriging)

    Article • Mathematical Geosciences, April 2013, Springer Science + Business Media

    Dr. Alexander Litvinenko

  29. Sampling from the low-cost surrogate model

    Article • January 2013, Springer Science + Business Media

    Dr. Alexander Litvinenko

  30. Bayesian Update of PCE coefficients

    Article • Journal of Computational Physics, July 2012, Elsevier

    Dr. Alexander Litvinenko

  31. A deterministic filter for non-Gaussian Bayesian estimation— Applications to dynamical system estimation with noisy measurements

    Article • Physica D Nonlinear Phenomena, April 2012, Elsevier

    Dr. Alexander Litvinenko

  32. Parametric and Uncertainty Computations with Tensor Product Representations

    Article • January 2012, Springer Science + Business Media

    Dr. Alexander Litvinenko

  33. How to approximate covariance matrices and Karhunen-Loeve expansion with a linear complexity.

    Article • Computing, October 2008, Springer Science + Business Media

    Dr. Alexander Litvinenko

  34. Data Sparse Computation of the Karhunen‐Loève Expansion

    Article • January 2008, American Institute of Physics

    Dr. Alexander Litvinenko

  35. Domain Decomposition Based H-Matrix Preconditioners for the Skin Problem

    Article • January 2008, Springer Science + Business Media

    Dr. Alexander Litvinenko

  36. Expert knowledge about classes increase the quality of the classifier

    Article • Pattern Recognition Letters, November 2003, Elsevier

    Dr. Alexander Litvinenko