Zobrazeno 1 - 10
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pro vyhledávání: '"Kritzer A"'
A control in feedback form is derived for linear quadratic, time-invariant optimal control problems subject to parabolic partial differential equations with coefficients depending on a countably infinite number of uncertain parameters. It is shown th
Externí odkaz:
http://arxiv.org/abs/2409.15537
Autor:
Anupindi, Vishnupriya, Kritzer, Peter
Digital nets provide an efficient way to generate integration nodes of quasi-Monte Carlo (QMC) rules. For certain applications, as e.g. in Uncertainty Quantification, we are interested in obtaining a speed-up in computing products of a matrix with th
Externí odkaz:
http://arxiv.org/abs/2406.10850
Autor:
Kritzer, Peter
We give an overview of certain aspects of tractability analysis of multivariate problems. This paper is not intended to give a complete account of the subject, but provides an insight into how the theory works for particular types of problems. We mai
Externí odkaz:
http://arxiv.org/abs/2402.02396
Autor:
Krieg, David, Kritzer, Peter
We consider linear problems in the worst case setting. That is, given a linear operator and a pool of admissible linear measurements, we want to approximate the values of the operator uniformly on a convex and balanced set by means of algorithms that
Externí odkaz:
http://arxiv.org/abs/2311.15767
A large literature specifies conditions under which the information complexity for a sequence of numerical problems defined for dimensions $1, 2, \ldots$ grows at a moderate rate, i.e., the sequence of problems is tractable. Here, we focus on the sit
Externí odkaz:
http://arxiv.org/abs/2310.17777
Let $f:[0,1]^d\to\mathbb{R}$ be a completely monotone integrand as defined by Aistleitner and Dick (2015) and let points $\boldsymbol{x}_0,\dots,\boldsymbol{x}_{n-1}\in[0,1]^d$ have a non-negative local discrepancy (NNLD) everywhere in $[0,1]^d$. We
Externí odkaz:
http://arxiv.org/abs/2309.04209
We study the approximation of integrals $\int_D f(\boldsymbol{x}^\top A) \mathrm{d} \mu(\boldsymbol{x})$, where $A$ is a matrix, by quasi-Monte Carlo (QMC) rules $N^{-1} \sum_{k=0}^{N-1} f(\boldsymbol{x}_k^\top A)$. We are interested in cases where t
Externí odkaz:
http://arxiv.org/abs/2305.11645
Autor:
Emily Banks, Vincent Francis, Sheng-Jia Lin, Fares Kharfallah, Vladimir Fonov, Maxime Lévesque, Chanshuai Han, Gopinath Kulasekaran, Marius Tuznik, Armin Bayati, Reem Al-Khater, Fowzan S. Alkuraya, Loukas Argyriou, Meisam Babaei, Melanie Bahlo, Behnoosh Bakhshoodeh, Eileen Barr, Lauren Bartik, Mahmoud Bassiony, Miriam Bertrand, Dominique Braun, Rebecca Buchert, Mauro Budetta, Maxime Cadieux-Dion, Daniel G. Calame, Heidi Cope, Donna Cushing, Stephanie Efthymiou, Marwa Abd Elmaksoud, Huda G. El Said, Tawfiq Froukh, Harinder K. Gill, Joseph G. Gleeson, Laura Gogoll, Elaine S.-Y. Goh, Vykuntaraju K. Gowda, Tobias B. Haack, Mais O. Hashem, Stefan Hauser, Trevor L. Hoffman, Jacob S. Hogue, Akimoto Hosokawa, Henry Houlden, Kevin Huang, Stephanie Huynh, Ehsan G. Karimiani, Silke Kaulfuß, G. Christoph Korenke, Amy Kritzer, Hane Lee, James R. Lupski, Elysa J. Marco, Kirsty McWalter, Arakel Minassian, Berge A. Minassian, David Murphy, Juanita Neira-Fresneda, Hope Northrup, Denis M. Nyaga, Barbara Oehl-Jaschkowitz, Matthew Osmond, Richard Person, Davut Pehlivan, Cassidy Petree, Lynette G. Sadleir, Carol Saunders, Ludger Schoels, Vandana Shashi, Rebecca C. Spillmann, Varunvenkat M. Srinivasan, Paria N. Torbati, Tulay Tos, Undiagnosed Diseases Network, Maha S. Zaki, Dihong Zhou, Christiane Zweier, Jean-François Trempe, Thomas M. Durcan, Ziv Gan-Or, Massimo Avoli, Cesar Alves, Gaurav K. Varshney, Reza Maroofian, David A. Rudko, Peter S. McPherson
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-22 (2024)
Abstract Developmental and epileptic encephalopathies (DEEs) feature altered brain development, developmental delay and seizures, with seizures exacerbating developmental delay. Here we identify a cohort with biallelic variants in DENND5A, encoding a
Externí odkaz:
https://doaj.org/article/67b9cc39749f4c32a8e5662c1d902770
Autor:
Kritzer, Peter, Osisiogu, Onyekachi
In this paper, we study an efficient algorithm for constructing point sets underlying quasi-Monte Carlo integration rules for weighted Korobov classes. The algorithm presented is a reduced fast component-by-component digit-by-digit (CBC-DBD) algorith
Externí odkaz:
http://arxiv.org/abs/2211.12237
Autor:
Kritzer, Peter
Lattice rules are among the most prominently studied quasi-Monte Carlo methods to approximate multivariate integrals. A rank-$1$ lattice rule to approximate an $s$-dimensional integral is fully specified by its \emph{generating vector} $\boldsymbol{z
Externí odkaz:
http://arxiv.org/abs/2208.13610