21 - 30 out of 276Page size: 10
Sort by: Title

  1. Вычислимые моделируемые преобразования декартовых координат для случайных векторов

    Abdrazakova, A. R. & Voytishek, A. V., Oct 2020, In: Journal of Computational Technologies. 25, 6, p. 62-84 23 p., 3.

    Research output: Contribution to journal › Article › peer-review

  2. Алгоритмы решения задач механики сплошной среды для экзафлопсных систем

    Snytnikov Aleksey, V. & Lazareva Galina, G., 2021, In: Journal of Computational Technologies. 26, 5, p. 81-94 14 p., 6.

    Research output: Contribution to journal › Article › peer-review

  3. Vector Monte Carlo algorithms with finite computational cost

    Medvedev, I. N., 20 Dec 2017, In: Russian Journal of Numerical Analysis and Mathematical Modelling. 32, 6, p. 359-370 12 p.

    Research output: Contribution to journal › Article › peer-review

  4. Using the inverse distribution function method and the modified superposition method in the NMPUD computer system

    Cherkashin, D. A. & Voytishek, A. V., 13 Dec 2021, In: Journal of Physics: Conference Series. 2099, 1, 012071.

    Research output: Contribution to journal › Conference article › peer-review

  5. Using maximum cross section method for filtering jump-diffusion random processes

    Averina, T. A. & Rybakov, K. A., 1 Apr 2020, In: Russian Journal of Numerical Analysis and Mathematical Modelling. 35, 2, p. 55-67 13 p.

    Research output: Contribution to journal › Article › peer-review

  6. Universal modification of vector weighted method of dependent trials

    Medvedev, I. N., 2022, In: Communications in Statistics: Simulation and Computation. 51, 2, p. 518-526 9 p.

    Research output: Contribution to journal › Article › peer-review

  7. Universal modification of vector weighted method of correlated sampling with finite computational cost

    Medvedev, I. N., 1 Feb 2019, In: Russian Journal of Numerical Analysis and Mathematical Modelling. 34, 1, p. 43-55 13 p.

    Research output: Contribution to journal › Article › peer-review

  8. Uncertainty quantification and stochastic polynomial chaos expansion for recovering random data in Darcy and Diffusion equations

    Shalimova, I. A., Sabelfeld, K. K. & Dulzon, O. V., 1 Dec 2017, In: Journal of Inverse and Ill-Posed Problems. 25, 6, p. 733-745 13 p.

    Research output: Contribution to journal › Article › peer-review

  9. Two variants of Monte Carlo projection method for numerical solution of nonlinear Boltzmann equation

    Rogasinsky, S. V., 1 Jun 2019, In: Russian Journal of Numerical Analysis and Mathematical Modelling. 34, 3, p. 143-150 8 p.

    Research output: Contribution to journal › Article › peer-review

  10. Two stochastic algorithms for solving elastostatics problems governed by the Lamé equation

    Kireeva, A., Aksyuk, I. & Sabelfeld, K. K., 1 Jun 2023, In: Monte Carlo Methods and Applications. 29, 2, p. 143-160 18 p.

    Research output: Contribution to journal › Article › peer-review

Previous 1 2 3 4 5 6 7 8 ...28 Next

ID: 3086447