Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Göpfert, Jan P."'
Engineering sciences, such as energy system research, play an important role in developing solutions to technical, environmental, economic, and social challenges of our modern society. In this context, the transformation of energy systems into climat
Externí odkaz:
http://arxiv.org/abs/2401.13365
Autor:
Kuckertz, Patrick, Göpfert, Jan, Karras, Oliver, Neuroth, David, Schönau, Julian, Pueblas, Rodrigo, Ferenz, Stephan, Engel, Felix, Pflugradt, Noah, Weinand, Jann M., Nieße, Astrid, Auer, Sören, Stolten, Detlef
The reuse of research software is central to research efficiency and academic exchange. The application of software enables researchers with varied backgrounds to reproduce, validate, and expand upon study findings. Furthermore, the analysis of open
Externí odkaz:
http://arxiv.org/abs/2306.10620
In recent years, large language models have achieved breakthroughs on a wide range of benchmarks in natural language processing and continue to increase in performance. Recently, the advances of large language models have raised interest outside the
Externí odkaz:
http://arxiv.org/abs/2306.09169
Autor:
Weinand, Jann Michael, Hoffmann, Maximilian, Göpfert, Jan, Terlouw, Tom, Schönau, Julian, Kuckertz, Patrick, McKenna, Russell, Kotzur, Leander, Linßen, Jochen, Stolten, Detlef
Recent global events emphasize the importance of a reliable energy supply. One way to increase energy supply security is through decentralized off-grid renewable energy systems, for which a growing number of case studies are researched. This review g
Externí odkaz:
http://arxiv.org/abs/2212.12742
Publikováno v:
IDEAL 2022, LNCS 13756, pp. 313-325, 2022
In modern business processes, the amount of data collected has increased substantially in recent years. Because this data can potentially yield valuable insights, automated knowledge extraction based on process mining has been proposed, among other t
Externí odkaz:
http://arxiv.org/abs/2212.00695
While Machine learning gives rise to astonishing results in automated systems, it is usually at the cost of large data requirements. This makes many successful algorithms from machine learning unsuitable for human-machine interaction, where the machi
Externí odkaz:
http://arxiv.org/abs/2012.13551
When training automated systems, it has been shown to be beneficial to adapt the representation of data by learning a problem-specific metric. This metric is global. We extend this idea and, for the widely used family of k nearest neighbors algorithm
Externí odkaz:
http://arxiv.org/abs/2011.03904
Autor:
Hindemith, Lukas, Vollmer, Anna-Lisa, Göpfert, Jan Phillip, Wiebel-Herboth, Christiane B., Wrede, Britta
Research in social robotics is commonly focused on designing robots that imitate human behavior. While this might increase a user's satisfaction and acceptance of robots at first glance, it does not automatically aid a non-expert user in naturally in
Externí odkaz:
http://arxiv.org/abs/2011.02731
Motivation: Innovative microfluidic systems carry the promise to greatly facilitate spatio-temporal analysis of single cells under well-defined environmental conditions, allowing novel insights into population heterogeneity and opening new opportunit
Externí odkaz:
http://arxiv.org/abs/2010.10124
Adversarial robustness of machine learning models has attracted considerable attention over recent years. Adversarial attacks undermine the reliability of and trust in machine learning models, but the construction of more robust models hinges on a ri
Externí odkaz:
http://arxiv.org/abs/2004.10882