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pro vyhledávání: '"Gebhardt, A."'
Publikováno v:
In Journal of Business Research November 2023 168
Akademický článek
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Autor:
Hurley, Dougal1, Gebhardt, Peter
Publikováno v:
Eureka Street. 9/10/2017, Vol. 27 Issue 18, p62-65. 4p.
Autor:
Li, Zhipeng, Gebhardt, Christoph, Inglin, Yves, Steck, Nicolas, Streli, Paul, Holz, Christian
Mixed Reality is increasingly used in mobile settings beyond controlled home and office spaces. This mobility introduces the need for user interface layouts that adapt to varying contexts. However, existing adaptive systems are designed only for stat
Externí odkaz:
http://arxiv.org/abs/2409.12836
Autor:
Gültekin, Kayhan, Gebhardt, Karl, Kormendy, John, Foord, Adi, Bender, Ralf, Lauer, Tod R., Pinkney, Jason, Richstone, Douglas O., Tremaine, Scott
We present IR photometry and HST imaging and spectroscopy of Sab galaxy NGC 4826. Schwarzschild dynamical modeling is used to measure its central black hole mass $M$. Photometric decomposition is used to enable a comparison of $M$ to published scalin
Externí odkaz:
http://arxiv.org/abs/2409.11575
Autor:
Cohn, Jonathan H., Curliss, Maeve, Walsh, Jonelle L., Kabasares, Kyle M., Boizelle, Benjamin D., Barth, Aaron J., Gebhardt, Karl, Gültekin, Kayhan, Buote, David A., Darling, Jeremy, Baker, Andrew J., Ho, Luis C.
We present 0$.\!\!^{\prime\prime}{22}$-resolution CO(2$-$1) observations of the circumnuclear gas disk in the local compact galaxy NGC 384 with the Atacama Large Millimeter/submillimeter Array (ALMA). While the majority of the disk displays regular r
Externí odkaz:
http://arxiv.org/abs/2409.08812
Autor:
House, Lindsay R., Gebhardt, Karl, Finkelstein, Keely, Cooper, Erin Mentuch, Davis, Dustin, Farrow, Daniel J., Schneider, Donald P.
We are merging a large participatory science effort with machine learning to enhance the Hobby-Eberly Telescope Dark Energy Experiment (HETDEX). Our overall goal is to remove false positives, allowing us to use lower signal-to-noise data and sources
Externí odkaz:
http://arxiv.org/abs/2409.08359
Autor:
N'dri, Antony W., Gebhardt, William, Teulière, Céline, Zeldenrust, Fleur, Rao, Rajesh P. N., Triesch, Jochen, Ororbia, Alexander
In this article, we review a class of neuro-mimetic computational models that we place under the label of spiking predictive coding. Specifically, we review the general framework of predictive processing in the context of neurons that emit discrete a
Externí odkaz:
http://arxiv.org/abs/2409.05386
Autor:
Pruisken, Insa
Publikováno v:
Soziologische Revue; Jan2022, Vol. 45 Issue 1, p124-128, 5p
Publikováno v:
Produktion. 5/18/2022, p26-26. 1p.