Zobrazeno 1 - 10
of 28
pro vyhledávání: '"Krake, Tim"'
Autor:
Klötzl, Daniel, Krake, Tim, Heyen, Frank, Becher, Michael, Koch, Maurice, Weiskopf, Daniel, Kurzhals, Kuno
The depiction of scanpaths from mobile eye-tracking recordings by thumbnails from the stimulus allows the application of visual computing to detect areas of interest in an unsupervised way. We suggest using nonnegative matrix factorization (NMF) to i
Externí odkaz:
http://arxiv.org/abs/2404.03417
Publikováno v:
Journal of Theoretical, Computational and Applied Mechanics (September 28, 2023) jtcam:11056
Large statically indeterminate truss and frame structures exhibit complex load-bearing behavior, and redundancy matrices are helpful for their analysis and design. Depending on the task, the full redundancy matrix or only its diagonal entries are req
Externí odkaz:
http://arxiv.org/abs/2303.03945
Autor:
Klötzl, Daniel, Krake, Tim, Zhou, Youjia, Stober, Jonathan, Schulte, Kathrin, Hotz, Ingrid, Wang, Bei, Weiskopf, Daniel
Publikováno v:
Topological Data Analysis and Visualization (TopoInVis) (2022) 39-48
We present a new topological connection method for the local bilinear computation of Jacobi sets that improves the visual representation while preserving the topological structure and geometric configuration. To this end, the topological structure of
Externí odkaz:
http://arxiv.org/abs/2208.07148
Autor:
Krake, Tim, von Scheven, Malte, Gade, Jan, Abdelaal, Moataz, Weiskopf, Daniel, Bischoff, Manfred
Publikováno v:
Journal of Theoretical, Computational and Applied Mechanics (November 11, 2022) jtcam:9615
Redundancy matrices provide insights into the load carrying behavior of statically indeterminate structures. This information can be employed for the design and analysis of structures with regard to certain objectives, for example reliability, robust
Externí odkaz:
http://arxiv.org/abs/2205.12264
Dynamic Mode Decomposition (DMD) is a data-driven and model-free decomposition technique. It is suitable for revealing spatio-temporal features of both numerically and experimentally acquired data. Conceptually, DMD performs a low-dimensional spectra
Externí odkaz:
http://arxiv.org/abs/2012.09633
Autor:
Enes, Kristina, Errami, Hassan, Wolter, Moritz, Krake, Tim, Eberhardt, Bernhard, Weber, Andreas, Zimmermann, Jörg
Various neural network based methods are capable of anticipating human body motions from data for a short period of time. What these methods lack are the interpretability and explainability of the network and its results. We propose to use Dynamic Mo
Externí odkaz:
http://arxiv.org/abs/1912.06688
Dynamic Mode Decomposition (DMD) is a data-driven decomposition technique extracting spatio-temporal patterns of time-dependent phenomena. In this paper, we perform a comprehensive theoretical analysis of various variants of DMD. We provide a systema
Externí odkaz:
http://arxiv.org/abs/1909.10466
Akademický článek
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Akademický článek
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Publikováno v:
Visual Computer; Sep2022, Vol. 38 Issue 9/10, p3435-3448, 14p
