Zobrazeno 1 - 10
of 25 154
pro vyhledávání: '"Findeisen, A."'
Autor:
Kosmovskaya Marina L.
Publikováno v:
Художественная культура, Iss 3, Pp 380-409 (2023)
The attempts to answer the question of what made outstanding figures of culture and art keep diaries lead to the conclusion that the reason for this systematic daily work was the awareness of fulfilling their own destiny, the search for which began i
Externí odkaz:
https://doaj.org/article/95f5da35491a410bb3067209bd6e5dc4
Autor:
N. Omanovic, S. Ferrachat, C. Fuchs, J. Henneberger, A. J. Miller, K. Ohneiser, F. Ramelli, P. Seifert, R. Spirig, H. Zhang, U. Lohmann
Publikováno v:
Atmospheric Chemistry and Physics, Vol 24, Pp 6825-6844 (2024)
The ice phase in clouds is essential for precipitation formation over continents. The underlying processes for ice growth are still poorly understood, leading to large uncertainties in precipitation forecasts and climate simulations. One crucial aspe
Externí odkaz:
https://doaj.org/article/b3e3d1b1884c47338e0c875be2b17bb7
Akademický článek
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Autor:
Findeisen, Janina
Publikováno v:
Paideuma: Mitteilungen zur Kulturkunde, 2009 Jan 01. 55, 179-199.
Externí odkaz:
https://www.jstor.org/stable/40342039
Autor:
Khain, Alexander1 (AUTHOR) alexander.khain@mail.huji.ac.il, Pinsky, M.1 (AUTHOR), Korolev, A.2 (AUTHOR)
Publikováno v:
Journal of the Atmospheric Sciences. Feb2022, Vol. 79 Issue 2, p383-407. 25p. 3 Color Photographs, 1 Diagram, 3 Charts, 12 Graphs.
Autor:
Huang, Yiyi1 (AUTHOR), Dong, Xiquan1 (AUTHOR) xdong@arizona.edu, Kay, Jennifer E.2 (AUTHOR), Xi, Baike1 (AUTHOR), McIlhattan, Elin A.3 (AUTHOR)
Publikováno v:
Climate Dynamics. May2021, Vol. 56 Issue 9/10, p3373-3394. 22p.
Closed-loop performance of sequential decision making algorithms, such as model predictive control, depends strongly on the parameters of cost functions, models, and constraints. Bayesian optimization is a common approach to learning these parameters
Externí odkaz:
http://arxiv.org/abs/2412.02423
Linear regression is often deemed inherently interpretable; however, challenges arise for high-dimensional data. We focus on further understanding how linear regression approximates nonlinear responses from high-dimensional functional data, motivated
Externí odkaz:
http://arxiv.org/abs/2411.12060
Autor:
Pfefferkorn, Maik, Findeisen, Rolf
Employing model predictive control to systems with unbounded, stochastic disturbances poses the challenge of guaranteeing safety, i.e., repeated feasibility and stability of the closed-loop system. Especially, there are no strict repeated feasibility
Externí odkaz:
http://arxiv.org/abs/2410.08186
We present a method, which allows efficient and safe approximation of model predictive controllers using kernel interpolation. Since the computational complexity of the approximating function scales linearly with the number of data points, we propose
Externí odkaz:
http://arxiv.org/abs/2410.06771