Zobrazeno 1 - 10
of 551
pro vyhledávání: '"Wallscheid, A."'
Autor:
Kirchgässner, Wilhelm, Förster, Nikolas, Piepenbrock, Till, Schweins, Oliver, Wallscheid, Oliver
The MagNet Challenge 2023 calls upon competitors to develop data-driven models for the material-specific, waveform-agnostic estimation of steady-state power losses in toroidal ferrite cores. The following HARDCORE (H-field and power loss estimation f
Externí odkaz:
http://arxiv.org/abs/2401.11488
Autor:
Peitz, Sebastian, Stenner, Jan, Chidananda, Vikas, Wallscheid, Oliver, Brunton, Steven L., Taira, Kunihiko
We present a convolutional framework which significantly reduces the complexity and thus, the computational effort for distributed reinforcement learning control of dynamical systems governed by partial differential equations (PDEs). Exploiting trans
Externí odkaz:
http://arxiv.org/abs/2301.10737
Autor:
Matteo Villa, David E. Sanin, Petya Apostolova, Mauro Corrado, Agnieszka M. Kabat, Carmine Cristinzio, Annamaria Regina, Gustavo E. Carrizo, Nisha Rana, Michal A. Stanczak, Francesc Baixauli, Katarzyna M. Grzes, Jovana Cupovic, Francesca Solagna, Alexandra Hackl, Anna-Maria Globig, Fabian Hässler, Daniel J. Puleston, Beth Kelly, Nina Cabezas-Wallscheid, Peter Hasselblatt, Bertram Bengsch, Robert Zeiser, Sagar, Joerg M. Buescher, Edward J. Pearce, Erika L. Pearce
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-19 (2024)
Abstract Immune cells must adapt to different environments during the course of an immune response. Here we study the adaptation of CD8+ T cells to the intestinal microenvironment and how this process shapes the establishment of the CD8+ T cell pool.
Externí odkaz:
https://doaj.org/article/94dc27161c6a48b2b42944d1f1be38af
Reinforcement learning (RL) is a promising, upcoming topic in automatic control applications. Where classical control approaches require a priori system knowledge, data-driven control approaches like RL allow a model-free controller design procedure,
Externí odkaz:
http://arxiv.org/abs/2201.13331
This review paper systematically summarizes the existing literature on utilizing machine learning (ML) techniques for the control and monitoring of electric machine drives. It is anticipated that with the rapid progress in learning algorithms and spe
Externí odkaz:
http://arxiv.org/abs/2110.05403
Autor:
Peitz, Sebastian, Stenner, Jan, Chidananda, Vikas, Wallscheid, Oliver, Brunton, Steven L., Taira, Kunihiko
Publikováno v:
In Physica D: Nonlinear Phenomena May 2024 461
Reinforcement learning (RL) is currently a popular research topic in control engineering and has the potential to make its way to industrial and commercial applications. Corresponding RL controllers are trained in direct interaction with the controll
Externí odkaz:
http://arxiv.org/abs/2105.08990
With electric power systems becoming more compact and increasingly powerful, the relevance of thermal stress especially during overload operation is expected to increase ceaselessly. Whenever critical temperatures cannot be measured economically on a
Externí odkaz:
http://arxiv.org/abs/2103.16323
Autor:
Anna-Maria Schaffer, Gina Jasmin Fiala, Miriam Hils, Eriberto Natali, Lmar Babrak, Laurenz Alexander Herr, Mari Carmen Romero-Mulero, Nina Cabezas-Wallscheid, Marta Rizzi, Enkelejda Miho, Wolfgang WA Schamel, Susana Minguet
Publikováno v:
eLife, Vol 13 (2024)
The ratio between κ and λ light chain (LC)-expressing B cells varies considerably between species. We recently identified Kinase D-interacting substrate of 220 kDa (Kidins220) as an interaction partner of the BCR. In vivo ablation of Kidins220 in B
Externí odkaz:
https://doaj.org/article/8e54cb9af4bb444790bb90fb84a3a4d3
Micro- and smart grids (MSG) play an important role both for integrating renewable energy sources in conventional electricity grids and for providing power supply in remote areas. Modern MSGs are largely driven by power electronic converters due to t
Externí odkaz:
http://arxiv.org/abs/2005.04869