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pro vyhledávání: '"MICHALOWICZ A"'
Autor:
Anthony, Quentin, Michalowicz, Benjamin, Hatef, Jacob, Xu, Lang, Abduljabbar, Mustafa, Shafi, Aamir, Subramoni, Hari, Panda, Dhabaleswar
Deep learning (DL) models based on the transformer architecture have revolutionized many DL applications such as large language models (LLMs), vision transformers, audio generation, and time series prediction. Much of this progress has been fueled by
Externí odkaz:
http://arxiv.org/abs/2408.10197
Autor:
Calder, A. C., Siegmann, E., Feldman, C., Chheda, S., Smolarski, D. C., Swesty, F. D., Curtis, A., Dey, J., Carlson, D., Michalowicz, B., Harrison, R. J.
We present a look at Ookami, a project providing community access to a testbed supercomputer with the ARM-based A64FX processors developed by a collaboration between RIKEN and Fujitsu and deployed in the Japanese supercomputer Fugaku. We describe the
Externí odkaz:
http://arxiv.org/abs/2311.04259
Autor:
Michalowicz, Benjamin, Raut, Eric, Kang, Yan, Curtis, Tony, Chapman, Barbara, Oryspayev, Dossay
The development of the A64FX processor by Fujitsu has created a massive innovation in High-Performance Computing and the birth of Fugaku: the current world's fastest supercomputer. A variety of tools are used to analyze the run-times and performances
Externí odkaz:
http://arxiv.org/abs/2107.10346
Autor:
Michalowicz, Benjamin, Raut, Eric, Kang, Yan, Curtis, Tony, Chapman, Barbara, Oryspayev, Dossay
The development of the A64FX processor by Fujitsu has been a massive innovation in vectorized processors and led to Fugaku: the current world's fastest supercomputer. We use a variety of tools to analyze the behavior and performance of several OpenMP
Externí odkaz:
http://arxiv.org/abs/2106.09787
Publikováno v:
In Chemosphere September 2023 335
Autor:
Xu, Jing, Bandyopadhyay, Dipankar, Mirzaei, Sedigheh, Michalowicz, Bryan, Chakraaborty, Bibhas
This paper proposes dynamic treatment regimes for choosing individualized effective treatment strategies of chronic periodontal disease. R codes for implementing the proposed sample size formula are available in GitHub.
Externí odkaz:
http://arxiv.org/abs/1902.09386
The recent interest in using deep learning for seismic interpretation tasks, such as facies classification, has been facing a significant obstacle, namely the absence of large publicly available annotated datasets for training and testing models. As
Externí odkaz:
http://arxiv.org/abs/1901.07659
Publikováno v:
In Science of the Total Environment 10 March 2022 811
Akademický článek
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Autor:
Michalowicz, Bryan S.1 (AUTHOR), Anderson, Jeffrey P.2 (AUTHOR), Kottke, Thomas E.1 (AUTHOR), Dehmer, Steven P.1 (AUTHOR), Worley, Donald C.1 (AUTHOR), Kane, Sheryl1 (AUTHOR), Basile, Sarah1 (AUTHOR), Rindal, D. Brad1 (AUTHOR) donald.b.rindal@healthpartners.com
Publikováno v:
PLoS ONE. 8/14/2023, Vol. 18 Issue 8, p1-16. 16p.