Zobrazeno 1 - 10
of 13 932
pro vyhledávání: '"Klar, A."'
Autor:
Weinbrenner, Paul, Klar, Patricia, Giese, Christian, Flacke, Luis, Müller, Manuel, Althammer, Matthias, Geprägs, Stephan, Gross, Rudolf, Reinhard, Friedemann
Planar scanning probe microscopy is a recently emerging alternative approach to tip-based scanning probe imaging. It can scan an extended planar sensor, such as a polished bulk diamond doped with magnetic-field-sensitive nitrogen-vacancy (NV) centers
Externí odkaz:
http://arxiv.org/abs/2409.04252
A flexible job shop scheduling problem (FJSSP) poses a complex optimization task in modeling real-world process scheduling tasks with conflicting objectives. To tackle FJSSPs, approximation methods are employed to ensure solutions are within acceptab
Externí odkaz:
http://arxiv.org/abs/2408.15671
Autor:
Lindenschmitt, Daniel, Seehofer, Paul, Schmitz, Marius, Mertes, Jan, Bless, Roland, Klar, Matthias, Zitterbart, Martina, Aurich, Jan C., Schotten, Hans D.
Flexible, self-organizing communication networks will be a key feature in the next mobile communication standard. Network-in-Network (NiN) is one important concept in 6G research, introducing sub-networks tailored to specific application requirements
Externí odkaz:
http://arxiv.org/abs/2408.14944
Autor:
Mariappan, Panchatchram, Willems, Klaas, Boregowda, Gangadhara, Tiwari, Sudarshan, Klar, Axel
In this paper, we present high-performance computing for the BGK model of the Boltzmann equations with a meshfree method. We use the Arbitrary-Lagrangian-Eulerian (ALE) method, where the approximation of spatial derivatives and the reconstruction of
Externí odkaz:
http://arxiv.org/abs/2408.02350
Autor:
Williams, Francis, Huang, Jiahui, Swartz, Jonathan, Klár, Gergely, Thakkar, Vijay, Cong, Matthew, Ren, Xuanchi, Li, Ruilong, Fuji-Tsang, Clement, Fidler, Sanja, Sifakis, Eftychios, Museth, Ken
We present fVDB, a novel GPU-optimized framework for deep learning on large-scale 3D data. fVDB provides a complete set of differentiable primitives to build deep learning architectures for common tasks in 3D learning such as convolution, pooling, at
Externí odkaz:
http://arxiv.org/abs/2407.01781
Autor:
Eberl, Andreas, Klar, Bernhard
Measuring dispersion is among the most fundamental and ubiquitous concepts in statistics, both in applied and theoretical contexts. In order to ensure that dispersion measures like the standard deviation indeed capture the dispersion of any given dis
Externí odkaz:
http://arxiv.org/abs/2406.02124
Autor:
Fischer, Florian, Ikkala, Aleksi, Klar, Markus, Fleig, Arthur, Bachinski, Miroslav, Murray-Smith, Roderick, Hämäläinen, Perttu, Oulasvirta, Antti, Müller, Jörg
Automated biomechanical testing has great potential for the development of VR applications, as initial insights into user behaviour can be gained in silico early in the design process. In particular, it allows prediction of user movements and ergonom
Externí odkaz:
http://arxiv.org/abs/2404.17695
Digital twinning of vehicles is an iconic application of digital twins, as the concept of twinning dates back to the twinning of NASA space vehicles. Although digital twins (DTs) in the automotive industry have been recognized for their ability to im
Externí odkaz:
http://arxiv.org/abs/2404.08438
Autor:
Holzmann, Hajo, Klar, Bernhard
We show that established performance metrics in binary classification, such as the F-score, the Jaccard similarity coefficient or Matthews' correlation coefficient (MCC), are not robust to class imbalance in the sense that if the proportion of the mi
Externí odkaz:
http://arxiv.org/abs/2404.07661
Multi-objective Quantum Annealing approach for solving flexible job shop scheduling in manufacturing
Publikováno v:
Journal of Manufacturing Systems Volume 72, February 2024, Pages 142-153
Flexible Job Shop Scheduling (FJSSP) is a complex optimization problem crucial for real-world process scheduling in manufacturing. Efficiently solving such problems is vital for maintaining competitiveness. This paper introduces Quantum Annealing-bas
Externí odkaz:
http://arxiv.org/abs/2311.09637