Zobrazeno 1 - 10
of 347
pro vyhledávání: '"Hans-Joachim Bungartz"'
Automatic gate-to-gate time recognition from audio recordings in slalom skiing using neural networks
Autor:
Friedrich Menhorn, Chris Hummel, Andreas Huber, Karlheinz Waibel, Hans-Joachim Bungartz, Peter Spitzenpfeil
Publikováno v:
Current Issues in Sport Science, Vol 9, Iss 3 (2024)
We introduce a novel approach for computing gate-to-gate time automatically from audio recordings. In slalom skiing, gate-to-gate timing is a valuable metric for athletes and trainers, capturing the time elapsed between slalom gates. The availability
Externí odkaz:
https://doaj.org/article/e54a1e7155c346f6bd80a7423bd316a9
Autor:
Kislaya Ravi, Vladyslav Fediukov, Felix Dietrich, Tobias Neckel, Fabian Buse, Michael Bergmann, Hans-Joachim Bungartz
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 4, p 045015 (2024)
One of the main challenges in surrogate modeling is the limited availability of data due to resource constraints associated with computationally expensive simulations. Multi-fidelity methods provide a solution by chaining models in a hierarchy with i
Externí odkaz:
https://doaj.org/article/c15fb50d403f474d8603fc120a370702
Autor:
Oguz Ziya Koseomur, Peter Vollmer, Kyle Davis, Gerasimos Chourdakis, Miriam Schulte, Benjamin Rodenberg, Benjamin Uekermann, Frédéric Simonis, Hans-Joachim Bungartz, Georg Abrams, Ishaan Desai, Lucia Cheung Yau, Richard Hertrich, Konrad Eder, Alexander Rusch, Florian Lindner, David Schneider, Dmytro Sashko, Dominik Volland, Amin Totounferoush
Publikováno v:
Open Research Europe, Vol 2 (2022)
preCICE is a free/open-source coupling library. It enables creating partitioned multi-physics simulations by gluing together separate software packages. This paper summarizes the development efforts in preCICE of the past five years. During this time
Externí odkaz:
https://doaj.org/article/70ddad740ef448bfaf924767a40de90f
Autor:
Oguz Ziya Koseomur, Peter Vollmer, Kyle Davis, Gerasimos Chourdakis, Miriam Schulte, Benjamin Rodenberg, Benjamin Uekermann, Frédéric Simonis, Hans-Joachim Bungartz, Georg Abrams, Ishaan Desai, Lucia Cheung Yau, Richard Hertrich, Konrad Eder, Alexander Rusch, Florian Lindner, David Schneider, Dmytro Sashko, Dominik Volland, Amin Totounferoush
Publikováno v:
Open Research Europe, Vol 2 (2022)
preCICE is a free/open-source coupling library. It enables creating partitioned multi-physics simulations by gluing together separate software packages. This paper summarizes the development efforts in preCICE of the past five years. During this time
Externí odkaz:
https://doaj.org/article/961e20261477413e95fc4dc6b47e7226
Publikováno v:
Data-Centric Engineering, Vol 2 (2021)
Model order reduction (MOR) methods enable the generation of real-time-capable digital twins, with the potential to unlock various novel value streams in industry. While traditional projection-based methods are robust and accurate for linear problems
Externí odkaz:
https://doaj.org/article/526f641640294973930003367ec5a6ec
Autor:
Christoph Riesinger, Arash Bakhtiari, Martin Schreiber, Philipp Neumann, Hans-Joachim Bungartz
Publikováno v:
Computation, Vol 5, Iss 4, p 48 (2017)
Heterogeneous clusters are a widely utilized class of supercomputers assembled from different types of computing devices, for instance CPUs and GPUs, providing a huge computational potential. Programming them in a scalable way exploiting the maximal
Externí odkaz:
https://doaj.org/article/4192d61ebea245719bf8865b4da455cc
Autor:
Atanas Atanasov, Benjamin Uekermann, Carlos A. Pachajoa Mejía, Hans-Joachim Bungartz, Philipp Neumann
Publikováno v:
Computation, Vol 4, Iss 4, p 38 (2016)
We present an Anderson acceleration-based approach to spatially couple three-dimensional Lattice Boltzmann and Navier–Stokes (LBNS) flow simulations. This allows to locally exploit the computational features of both fluid flow solver approaches to
Externí odkaz:
https://doaj.org/article/c23b45725a6c42629df5c3ae8f0869cd
This open access book summarizes the research done and results obtained in the second funding phase of the Priority Program 1648'Software for Exascale Computing'(SPPEXA) of the German Research Foundation (DFG) presented at the SPPEXA Symposium in Dre
Publikováno v:
Journal of Computational and Applied Mathematics. 433:115278
Publikováno v:
Parallel Processing and Applied Mathematics ISBN: 9783031304415
Training deep neural networks consumes increasing computational resource shares in many compute centers. Often, a brute force approach to obtain hyperparameter values is employed. Our goal is (1) to enhance this by enabling second-order optimization
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38ee88ff3b1ff2e7815e29c97eb0bedd
https://doi.org/10.1007/978-3-031-30442-2_11
https://doi.org/10.1007/978-3-031-30442-2_11