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Dr Vesa Kaarnioja

Adjunct Associate Lecturer
Science
School of Mathematics & Statistics
  • Book Chapters | 2024
    Guth PA; Kaarnioja V, 2024, 'Application of Dimension Truncation Error Analysis to High-Dimensional Function Approximation in Uncertainty Quantification', in , pp. 297 - 312, http://dx.doi.org/10.1007/978-3-031-59762-6_14
    Book Chapters | 2024
    Kaarnioja V; Kuo FY; Sloan IH, 2024, 'Lattice-Based Kernel Approximation and Serendipitous Weights for Parametric PDEs in Very High Dimensions', in , pp. 81 - 103, http://dx.doi.org/10.1007/978-3-031-59762-6_4
  • Journal articles | 2024
    Guth PA; Kaarnioja V; Kuo FY; Schillings C; Sloan IH, 2024, 'Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration', Numerische Mathematik, 156, pp. 565 - 608, http://dx.doi.org/10.1007/s00211-024-01397-9
    Journal articles | 2024
    Guth PA; Kaarnioja V, 2024, 'GENERALIZED DIMENSION TRUNCATION ERROR ANALYSIS FOR HIGH-DIMENSIONAL NUMERICAL INTEGRATION: LOGNORMAL SETTING AND BEYOND', SIAM Journal on Numerical Analysis, 62, pp. 775 - 810, http://dx.doi.org/10.1137/23m1593188
    Journal articles | 2024
    Hakula H; Harbrecht H; Kaarnioja V; Kuo FY; Sloan IH, 2024, 'Uncertainty quantification for random domains using periodic random variables', Numerische Mathematik, 156, pp. 273 - 317, http://dx.doi.org/10.1007/s00211-023-01392-6
    Journal articles | 2022
    Kaarnioja V; Kazashi Y; Kuo FY; Nobile F; Sloan IH, 2022, 'Fast approximation by periodic kernel-based lattice-point interpolation with application in uncertainty quantification', Numerische Mathematik, 150, pp. 33 - 77, http://dx.doi.org/10.1007/s00211-021-01242-3
    Journal articles | 2021
    Guth PA; Kaarnioja V; Kuo FY; Schillings C; Sloan IH, 2021, 'A quasi-monte carlo method for optimal control under uncertainty', SIAM-ASA Journal on Uncertainty Quantification, 9, pp. 354 - 383, http://dx.doi.org/10.1137/19M1294952
    Journal articles | 2021
    Kaarnioja V, 2021, 'Bounds on the spectrum of nonsingular triangular (0,1)-matrices', Journal of Combinatorial Theory. Series A, 178, http://dx.doi.org/10.1016/j.jcta.2020.105353
    Journal articles | 2020
    Kaarnioja V; Kuo FY; Sloan IH, 2020, 'Uncertainty quantification using periodic random variables', SIAM Journal on Numerical Analysis, 58, pp. 1068 - 1091, http://dx.doi.org/10.1137/19M1262796
    Journal articles | 2018
    Hakula H; Kaarnioja V; Laaksonen M; Aly AM, 2018, 'Cylindrical Shell with Junctions: Uncertainty Quantification of Free Vibration and Frequency Response Analysis', Shock and Vibration, 2018, http://dx.doi.org/10.1155/2018/5817940
    Journal articles | 2018
    Ilmonen P; Kaarnioja V, 2018, 'Generalized eigenvalue problems for meet and join matrices on semilattices', Linear Algebra and Its Applications, 536, pp. 250 - 273, http://dx.doi.org/10.1016/j.laa.2017.09.023
    Journal articles | 2017
    Hyvönen N; Kaarnioja V; Mustonen L; Staboulis S, 2017, 'Polynomial collocation for handling an inaccurately known measurement configuration in electrical impedance tomography', SIAM Journal on Applied Mathematics, 77, pp. 202 - 223, http://dx.doi.org/10.1137/16M1068888
  • Preprints | 2023
    Kaarnioja V; Kuo FY; Sloan IH, 2023, Lattice-based kernel approximation and serendipitous weights for parametric PDEs in very high dimensions, http://arxiv.org/abs/2303.17755v2
    Preprints | 2023
    Sloan IH; Kaarnioja V, 2023, Doubling the rate -- improved error bounds for orthogonal projection with application to interpolation, http://arxiv.org/abs/2308.06052v3
    Preprints | 2023
    2023, Application of dimension truncation error analysis to high-dimensional function approximation, , http://dx.doi.org/10.48550/arxiv.2301.13693
    Preprints | 2022
    Guth PA; Kaarnioja V; Kuo FY; Schillings C; Sloan IH, 2022, Parabolic PDE-constrained optimal control under uncertainty with entropic risk measure using quasi-Monte Carlo integration, http://dx.doi.org/10.1007/s00211-024-01397-9
    Preprints | 2022
    Hakula H; Harbrecht H; Kaarnioja V; Kuo FY; Sloan IH, 2022, Uncertainty quantification for random domains using periodic random variables, http://arxiv.org/abs/2210.17329v2
    Preprints | 2022
    Hakula H; Harbrecht H; Kaarnioja V; Kuo FY; Sloan IH, 2022, Uncertainty quantification for random domains using periodic random variables, http://dx.doi.org/10.48550/arxiv.2210.17329
    Preprints | 2022
    2022, Generalized dimension truncation error analysis for high-dimensional numerical integration: lognormal setting and beyond, , http://dx.doi.org/10.48550/arxiv.2209.06176
    Preprints | 2022
    2022, Quasi-Monte Carlo and discontinuous Galerkin, , http://dx.doi.org/10.48550/arxiv.2207.07698
    Preprints | 2020
    Kaarnioja V; Kazashi Y; Kuo FY; Nobile F; Sloan IH, 2020, Fast approximation by periodic kernel-based lattice-point interpolation with application in uncertainty quantification, http://dx.doi.org/10.48550/arxiv.2007.06367
    Preprints | 2020
    2020, Bounds on the spectrum of nonsingular triangular $(0,1)$-matrices, , http://dx.doi.org/10.48550/arxiv.2002.03337
    Preprints | 2019
    Guth PA; Kaarnioja V; Kuo FY; Schillings C; Sloan IH, 2019, A quasi-Monte Carlo Method for an Optimal Control Problem Under Uncertainty, http://dx.doi.org/10.48550/arxiv.1910.10022
    Preprints | 2018
    2018, Positive definite functions on semilattices, , http://dx.doi.org/10.48550/arxiv.1804.03047
    Preprints | 2017
    2017, Computation of extremal eigenvalues of high-dimensional lattice-theoretic tensors via tensor-train decompositions, , http://dx.doi.org/10.48550/arxiv.1705.05163
    Preprints | 2017
    2017, Generalized eigenvalue problems for meet and join matrices on semilattices, , http://dx.doi.org/10.48550/arxiv.1705.05169
    Preprints | 2017
    2017, On the structure of join tensors with applications to tensor eigenvalue problems, , http://dx.doi.org/10.48550/arxiv.1705.06313
    Preprints | 2016
    2016, Polynomial collocation for handling an inaccurately known measurement configuration in electrical impedance tomography, , http://dx.doi.org/10.48550/arxiv.1604.00353
    Conference Papers | 2015
    Hakula H; Kaarnioja V; Laaksonen M, 2015, 'Approximate methods for stochastic eigenvalue problems', in Applied Mathematics and Computation, pp. 664 - 681, http://dx.doi.org/10.1016/j.amc.2014.12.112
    Preprints | 2015
    2015, On applying the maximum volume principle to a basis selection problem in multivariate polynomial interpolation, , http://dx.doi.org/10.48550/arxiv.1512.07424