Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Philipp Trunschke"'
Publikováno v:
Frontiers in Applied Mathematics and Statistics, Vol 7 (2021)
Low-rank tensors are an established framework for the parametrization of multivariate polynomials. We propose to extend this framework by including the concept of block-sparsity to efficiently parametrize homogeneous, multivariate polynomials with lo
Externí odkaz:
https://doaj.org/article/cb05f16a7e2943c4b61d19aed1e6f3ab
An efficient compression technique based on hierarchical tensors for popular option pricing methods is presented. It is shown that the "curse of dimensionality" can be alleviated for the computation of Bermudan option prices with the Monte Carlo leas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e9f390535cc148624a8687ec0746e4e8
Autor:
Ezgi Erdem, Gregor Koch, Jutta Kröhnert, Raoul Naumann d'Alnoncourt, Detre Teschner, Thomas Lunkenbein, Gregory S. Huff, Robert Schlögl, Spencer J. Carey, Rania Hanna, Philipp Trunschke, Frederik Rüther, Pierre Kube, Stephen Lohr, Olaf Timpe, Andrey Tarasov, Christoph Pratsch, Maike Hashagen, Matthias Scheffler, Peter Kraus, Wiebke Frandsen, Frank Girgsdies, Maxime Boniface, Liudmyla Masliuk, Sabine Wrabetz, Annette Trunschke, Yuanqing Wang, Axel Knop-Gericke, Toyin Omojola, Luca M. Ghiringhelli, Lucas Foppa, Frank Rosowski, Michael Hävecker, Jinhu Dong, Sven Richter, Giulia Bellini, Christian Rohner, Michael Geske
Publikováno v:
Topics in Catalysis
The “Seven Pillars” of oxidation catalysis proposed by Robert K. Grasselli represent an early example of phenomenological descriptors in the field of heterogeneous catalysis. Major advances in the theoretical description of catalytic reactions ha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8169cdc72a1815589ce69e2154ed66c
https://hdl.handle.net/21.11116/0000-0007-4265-D21.11116/0000-0007-9CA6-E
https://hdl.handle.net/21.11116/0000-0007-4265-D21.11116/0000-0007-9CA6-E
We consider best approximation problems in a nonlinear subset $\mathcal{M}$ of a Banach space of functions $(\mathcal{V},\|\bullet\|)$. The norm is assumed to be a generalization of the $L^2$-norm for which only a weighted Monte Carlo estimate $\|\bu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fad58ab2ad7bfd7c0bb3e6af99b945bf
A statistical learning approach for high-dimensional parametric PDEs related to uncertainty quantification is derived. The method is based on the minimization of an empirical risk on a selected model class, and it is shown to be applicable to a broad
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::210a44a63a3e947d69b3b02e3dc42ab8
http://arxiv.org/abs/1810.01348
http://arxiv.org/abs/1810.01348
Publikováno v:
Operations Research Proceedings ISBN: 9783319899190
OR
OR
We present a concept that provides an efficient description of differential-algebraic equations (DAEs) describing flow networks which provides the DAE function \(f\) and their Jacobians in an automatized way such that the sparsity pattern of the Jaco
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::29cc03c2d385b590df1f7b70b5bc21e9
https://doi.org/10.1007/978-3-319-89920-6_83
https://doi.org/10.1007/978-3-319-89920-6_83