Zobrazeno 1 - 10 of 120 pro vyhledávání: '"Markus Hegland"'
1
The combination technique applied to functionals
Autor: Yuancheng Zhou, Markus Hegland
Publikováno v: ANZIAM Journal. 62:C208-C224
Functionals related to a solution of a problem, usually modelled by partial differential equations, can be important quantities used to capture features of the problem. For high dimensional problems the computational cost of the functionals can be la
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::8a442d67e96078b830acb4864ebf04fb
https://doi.org/10.21914/anziamj.v62.16112
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2
Low rank approximation of positive semi-definite symmetric matrices using Gaussian elimination and volume sampling
Autor: Markus Hegland, Frank De Hoog
Publikováno v: ANZIAM Journal. 62:C58-C71
Positive semi-definite matrices commonly occur as normal matrices of least squares problems in statistics or as kernel matrices in machine learning and approximation theory. They are typically large and dense. Thus algorithms to solve systems with su
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d2dd95fb2b399367885f1e2dbc534d7c
https://doi.org/10.21914/anziamj.v62.16036
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3
A Note on Error Bounds for Pseudo Skeleton Approximations of Matrices
Autor: Frank de Hoog, Markus Hegland
Due to their importance in both data analysis and numerical algorithms, low rank approximations have recently been widely studied. They enable the handling of very large matrices. Tight error bounds for the computationally efficient Gaussian eliminat
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc16aed79bd87d371193ce301ac12314
http://arxiv.org/abs/2107.01819
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4
Numerical methods for computing the greatest common divisor of univariate polynomials using floating point arithmetic
Autor: Markus Hegland
Publikováno v: ANZIAM Journal. 60:C127-C139
Computing the greatest common divisor (GCD) for two polynomials in floating point arithmetic is computationally challenging and even standard library software might return the result GCD=1 even when the polynomials have a nontrivial GCD. Here we revi
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::f19bbd8e368e5717929de5e2c46765c5
https://doi.org/10.21914/anziamj.v60i0.14059
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5
Numerical integration of particle orbits in discontinuous fields using VENUS-LEVIS and SPEC
Autor: David Pfefferlé, Zhisong Qu, Markus Hegland, Matthew Hole, Dean Muir
Publikováno v: Computer Physics Communications. 271:108191
The orbit code VENUS-LEVIS is adapted to follow particles in plasma equilibria with discontinuous fields generated by the Stepped Pressure Equilibrium Code (SPEC). The latter is an implementation of the Multi-Region relaxed MHD model, which efficient
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cc22757559f640e303f781607a4bc66b
https://doi.org/10.1016/j.cpc.2021.108191
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7
Stratified space learning: Reconstructing embedded graphs
Autor: Yossi Bleile, Markus Hegland
Publikováno v: Bokor, Y 2019, Stratified space learning: Reconstructing embedded graphs . i El Sawah, S. (ed.) MODSIM2019, 23rd International Congress on Modelling and Simulation. . https://doi.org/10.36334/modsim.2019.a3.bokor
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2fa2897563c69321e752fd3c44833ab4
https://vbn.aau.dk/da/publications/da1829a3-f326-410c-9597-7b389883cace
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8
Old wine in fractal bottles I: Orthogonal expansions on self-referential spaces via fractal transformations
Autor: Michael F. Barnsley, Markus Hegland, Christoph Bandt, Andrew Vince
Publikováno v: Chaos, Solitons & Fractals. 91:478-489
Our results and examples show how transformations between self-similar sets may be continuous almost everywhere with respect to measures on the sets and may be used to carry well known notions from analysis and functional analysis, for example flows
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https://doi.org/10.1016/j.chaos.2016.07.007
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9
Complex scientific applications made fault-tolerant with the sparse grid combination technique
Autor: Brendan Harding, Markus Hegland, Peter Strazdins, Mohsin Ali
Publikováno v: The International Journal of High Performance Computing Applications. 30:335-359
Ultra-large–scale simulations via solving partial differential equations (PDEs) require very large computational systems for their timely solution. Studies shown the rate of failure grows with the system size, and these trends are likely to worsen
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::22f68f9640d0b576eb1ca21b8f4e1cd3
https://doi.org/10.1177/1094342015628056
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10
Fault Tolerant Computation with the Sparse Grid Combination Technique
Autor: James Southern, Jay Larson, Brendan Harding, Markus Hegland
Publikováno v: SIAM Journal on Scientific Computing. 37:C331-C353
This paper continues to develop a fault tolerant extension of the sparse grid combination technique recently proposed in [B. Harding and M. Hegland, ANZIAM J. Electron. Suppl., 54 (2013), pp. C394--C411]. This approach to fault tolerance is novel for
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::147be0d0bd7f98b9ccfcc6d1aee46d73
https://doi.org/10.1137/140964448
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