Zobrazeno 1 - 10
of 533
pro vyhledávání: '"Jorgensen, P. S."'
Autor:
Papoutsellis, Evangelos, da Costa-Luis, Casper, Deidda, Daniel, Delplancke, Claire, Duff, Margaret, Fardell, Gemma, Gillman, Ashley, Jørgensen, Jakob S., Kereta, Zeljko, Ovtchinnikov, Evgueni, Pasca, Edoardo, Schramm, Georg, Thielemans, Kris
We introduce a stochastic framework into the open--source Core Imaging Library (CIL) which enables easy development of stochastic algorithms. Five such algorithms from the literature are developed, Stochastic Gradient Descent, Stochastic Average Grad
Externí odkaz:
http://arxiv.org/abs/2406.15159
Autor:
Seelinger, Linus, Reinarz, Anne, Lykkegaard, Mikkel B., Akers, Robert, Alghamdi, Amal M. A., Aristoff, David, Bangerth, Wolfgang, Bénézech, Jean, Diez, Matteo, Frey, Kurt, Jakeman, John D., Jørgensen, Jakob S., Kim, Ki-Tae, Kent, Benjamin M., Martinelli, Massimiliano, Parno, Matthew, Pellegrini, Riccardo, Petra, Noemi, Riis, Nicolai A. B., Rosenfeld, Katherine, Serani, Andrea, Tamellini, Lorenzo, Villa, Umberto, Dodwell, Tim J., Scheichl, Robert
Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-l
Externí odkaz:
http://arxiv.org/abs/2402.13768
Autor:
Jørgensen, P. S., Besley, L., Slyamov, A. M., Diaz, A., Guizar-Sicairos, M., Odstrcil, M., Holler, M., Silvestre, C., Chang, B., Detlefs, C., Andreasen, J. W.
We demonstrate a technique that allows highly surface sensitive imaging of nanostructures on planar surfaces over large areas, providing a new avenue for research in materials science, especially for \textit{in situ} applications. The capabilities of
Externí odkaz:
http://arxiv.org/abs/2307.01735
Autor:
Alghamdi, Amal M A, Riis, Nicolai A B, Afkham, Babak M, Uribe, Felipe, Christensen, Silja L, Hansen, Per Christian, Jørgensen, Jakob S
Inverse problems, particularly those governed by Partial Differential Equations (PDEs), are prevalent in various scientific and engineering applications, and uncertainty quantification (UQ) of solutions to these problems is essential for informed dec
Externí odkaz:
http://arxiv.org/abs/2305.16951
Autor:
Riis, Nicolai A B, Alghamdi, Amal M A, Uribe, Felipe, Christensen, Silja L, Afkham, Babak M, Hansen, Per Christian, Jørgensen, Jakob S
This paper introduces CUQIpy, a versatile open-source Python package for computational uncertainty quantification (UQ) in inverse problems, presented as Part I of a two-part series. CUQIpy employs a Bayesian framework, integrating prior knowledge wit
Externí odkaz:
http://arxiv.org/abs/2305.16949
Autor:
Bangsgaard, Katrine O, Burca, Genoveva, Ametova, Evelina, Andersen, Martin S, Jørgensen, Jakob S
Spectral computed tomography has received considerable interest in recent years since spectral measurements contain much richer information about the object of interest. In spectral computed tomography, we are interested in the energy channel-wise re
Externí odkaz:
http://arxiv.org/abs/2203.01637
Computed tomography is a method for synthesizing volumetric or cross-sectional images of an object from a collection of projections. Popular reconstruction methods for computed tomography are based on idealized models and assumptions that may not be
Externí odkaz:
http://arxiv.org/abs/2203.01045
A non-destructive testing (NDT) application of X-ray computed tomography (CT) is inspection of subsea pipes in operation via 2D cross-sectional scans. Data acquisition is time-consuming and costly due to the challenging subsea environment. Reducing t
Externí odkaz:
http://arxiv.org/abs/2203.01030
The generalized minimal residual (GMRES) algorithm is applied to image reconstruction using linear computed tomography (CT) models. The GMRES algorithm iteratively solves square, non-symmetric linear systems and it has practical application to CT whe
Externí odkaz:
http://arxiv.org/abs/2201.07408
Autor:
Tang, Nan, Quigley, Lizabeth, Boldman, Walker L., Jorgensen, Cameron S., Koch, Rémi, O'Leary, Daniel, Meda, Hugh R., Rack, Philip D., Gilbert, Dustin A.
Publikováno v:
Phys. Rev. Materials 5, 114405 (2021)
Compositionally complex materials (CCMs) present a potential paradigm shift in the design of magnetic materials. These alloys exhibit long-range structural order coupled with limited or no chemical order. As a result, extreme local environments exist
Externí odkaz:
http://arxiv.org/abs/2111.12188