Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Farchmin, Nando"'
Numerical methods for random parametric PDEs can greatly benefit from adaptive refinement schemes, in particular when functional approximations are computed as in stochastic Galerkin and stochastic collocations methods. This work is concerned with a
Externí odkaz:
http://arxiv.org/abs/2112.01285
In this work a general approach to compute a compressed representation of the exponential $\exp(h)$ of a high-dimensional function $h$ is presented. Such exponential functions play an important role in several problems in Uncertainty Quantification,
Externí odkaz:
http://arxiv.org/abs/2105.09064
Autor:
Andrle, Anna, Farchmin, Nando, Hagemann, Paul, Heidenreich, Sebastian, Soltwisch, Victor, Steidl, Gabriele
Grazing incidence X-ray fluorescence is a non-destructive technique for analyzing the geometry and compositional parameters of nanostructures appearing e.g. in computer chips. In this paper, we propose to reconstruct the posterior parameter distribut
Externí odkaz:
http://arxiv.org/abs/2102.03189
Autor:
Farchmin, Nando, Hammerschmidt, Martin, Schneider, Philipp-Immanuel, Wurm, Matthias, Bodermann, Bernd, Bär, Markus, Heidenreich, Sebastian
Publikováno v:
J. Micro/Nanolith. MEMS MOEMS 19(2), 024001 (2020)
Background: Scatterometry is a fast, indirect and non-destructive optical method for quality control in the production of lithography masks. To solve the inverse problem in compliance with the upcoming need for improved accuracy, a computationally ex
Externí odkaz:
http://arxiv.org/abs/2005.05164
Autor:
Farchmin, Nando, Hammerschmidt, Martin, Schneider, Philipp-Immanuel, Wurm, Matthias, Bodermann, Bernd, Bär, Markus, Heidenreich, Sebastian
Publikováno v:
Proc. SPIE 11057, Modeling Aspects in Optical Metrology VII, 110570J (21 June 2019)
Scatterometry is a fast, indirect and nondestructive optical method for the quality control in the production of lithography masks. Geometry parameters of line gratings are obtained from diffracted light intensities by solving an inverse problem. To
Externí odkaz:
http://arxiv.org/abs/1910.14435
Autor:
Alfke, Dominik, Baines, Weston, Blechschmidt, Jan, Sarmina, Mauricio J. del Razo, Drory, Amnon, Elbrächter, Dennis, Farchmin, Nando, Gambara, Matteo, Glas, Silke, Grohs, Philipp, Hinz, Peter, Kivaranovic, Danijel, Kümmerle, Christian, Kutyniok, Gitta, Lunz, Sebastian, Macdonald, Jan, Malthaner, Ryan, Naisat, Gregory, Neufeld, Ariel, Petersen, Philipp Christian, Reisenhofer, Rafael, Sheng, Jun-Da, Thesing, Laura, Trunschke, Philipp, von Lindheim, Johannes, Weber, David, Weber, Melanie
We present a novel technique based on deep learning and set theory which yields exceptional classification and prediction results. Having access to a sufficiently large amount of labelled training data, our methodology is capable of predicting the la
Externí odkaz:
http://arxiv.org/abs/1901.05744
Autor:
Eigel, Martin, Farchmin, Nando
Solving high-dimensional random parametric PDEs poses a challenging computational problem. It is well-known that numerical methods can greatly benefit from adaptive refinement algorithms, in particular when functional approximations in polynomials ar
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f401341adaaa466dacf6a88c9bc0837
Publikováno v:
SIAM Journal on Scientific Computing; 2023, Vol. 45 Issue 2, pA457-A479, 23p
Autor:
Winkler, Benjamin, Nagel, Claudia, Farchmin, Nando, Heidenreich, Sebastian, Loewe, Axel, Dössel, Olaf, Bär, Markus
Publikováno v:
Metrology; 2023, Vol. 3 Issue 1, p1-28, 28p