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pro vyhledávání: '"Schenkels, Nick"'
Tikhonov regularization is a popular approach to obtain a meaningful solution for ill-conditioned linear least squares problems. A relatively simple way of choosing a good regularization parameter is given by Morozov's discrepancy principle. However,
Externí odkaz:
http://arxiv.org/abs/1910.08432
Autor:
Schenkels, Nick, Vanroose, Wim
In this paper we derive a Newton type method to solve the non-linear system formed by combining the Tikhonov normal equations and Morozov's discrepancy principle. We prove that by placing a bound on the step size of the Newton iterations the method w
Externí odkaz:
http://arxiv.org/abs/1809.01627
Autor:
Schenkels, Nick, Vanroose, Wim
Many inverse problems can be described by a PDE model with unknown parameters that need to be calibrated based on measurements related to its solution. This can be seen as a constrained minimization problem where one wishes to minimize the mismatch b
Externí odkaz:
http://arxiv.org/abs/1804.04542
Phase contrast tomography is an alternative to classic absorption contrast tomography that leads to higher contrast reconstructions in many applications. We review how phase contrast data can be acquired by using a combination of phase and absorption
Externí odkaz:
http://arxiv.org/abs/1510.03233
Autor:
Schenkels, Nick, Vanroose, Wim
Publikováno v:
In Journal of Computational and Applied Mathematics 1 March 2019 348:14-25
Autor:
Agullo, Emmanuel, Cools, Siegfried, Fatih-Yetkin, Emrullah, Giraud, Luc, Schenkels, Nick, Vanroose, Wim
Publikováno v:
[Research Report] RR-9360, Inria Bordeaux Sud-Ouest. 2020
This note is a follow up study to [1], where we studied the resilience of the preconditioned conjugate gradient method (PCG). We complement the original work by performinga similar series of numerical experiments, but using what we called persistent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::c84118932862be6a604ed2f0cbaa6059
https://hal.inria.fr/hal-02921669v2/document
https://hal.inria.fr/hal-02921669v2/document
Publikováno v:
[Research Report] RR-9342, Inria Bordeaux Sud-Ouest. 2020
Large scale applications running on HPC systems often require a substantial amount of memory and can have a large computational overhead. Lossy data compression techniques can reduce the size of the data and associated communication cost, but the eff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b76b1850a660f9dd104f1684023430bf
https://inria.hal.science/hal-02572910
https://inria.hal.science/hal-02572910
On soft errors in the Conjugate Gradient method: sensitivity and robust numerical detection -revised
Autor:
Agullo, Emmanuel, Cools, Siegfried, Fatih-Yetkin, Emrullah, Giraud, Luc, Schenkels, Nick, Vanroose, Wim
Publikováno v:
[Research Report] RR-9330, Inria Bordeaux Sud-Ouest. 2020, pp.43
[Research Report] RR-9330, Inria Bordeaux Sud-Ouest. 2020, pp.31
[Research Report] RR-9330, Inria Bordeaux Sud-Ouest. 2020, pp.31
The conjugate gradient (CG) method is the most widely used iterative scheme forthe solution of large sparse systems of linear equations when the matrix is symmetric positivedefinite. Although more than sixty year old, it is still a serious candidate
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::483cbfa5144712553f028373ca852a32
https://hal.inria.fr/hal-02495301v3/document
https://hal.inria.fr/hal-02495301v3/document
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