Zobrazeno 1 - 10
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pro vyhledávání: '"Henschel, P"'
We present the first study of the Public Register of Licensed Persons and Registered Institutions maintained by the Hong Kong Securities and Futures Commission (SFC) through the lens of complex network analysis. This dataset, spanning 21 years with d
Externí odkaz:
http://arxiv.org/abs/2410.07970
Autor:
AlNuaimi, Khaled, Marti, Gautier, Ravaut, Mathieu, AlKetbi, Abdulla, Henschel, Andreas, Jaradat, Raed
Enriching datasets with demographic information, such as gender, race, and age from names, is a critical task in fields like healthcare, public policy, and social sciences. Such demographic insights allow for more precise and effective engagement wit
Externí odkaz:
http://arxiv.org/abs/2409.11491
Autor:
Henschel, Robert, Lindemann, Jonas, Follin, Anders, Dammann, Bernd, Dennis, Cicada, Thota, Abhinav
High Performance Research Desktops are used by HPC centers and research computing organizations to lower the barrier of entry to HPC systems. These Linux desktops are deployed alongside HPC systems, leveraging the investments in HPC compute and stora
Externí odkaz:
http://arxiv.org/abs/2404.03298
Autor:
Henschel, Roberto, Khachatryan, Levon, Hayrapetyan, Daniil, Poghosyan, Hayk, Tadevosyan, Vahram, Wang, Zhangyang, Navasardyan, Shant, Shi, Humphrey
Text-to-video diffusion models enable the generation of high-quality videos that follow text instructions, making it easy to create diverse and individual content. However, existing approaches mostly focus on high-quality short video generation (typi
Externí odkaz:
http://arxiv.org/abs/2403.14773
Autor:
Reuther, Albert, Brown, Nick, Arndt, William, Blaschke, Johannes, Boehme, Christian, Chazapis, Antony, Enders, Bjoern, Henschel, Robert, Kunkel, Julian, Martinasso, Maxime
As a broader set of applications from simulations to data analysis and machine learning require more parallel computational capability, the demand for interactive and urgent high performance computing (HPC) continues to increase. This paper overviews
Externí odkaz:
http://arxiv.org/abs/2401.14550
Autor:
Li, Jiachen, Henschel, Roberto, Goel, Vidit, Ohanyan, Marianna, Navasardyan, Shant, Shi, Humphrey
Conventional video matting outputs one alpha matte for all instances appearing in a video frame so that individual instances are not distinguished. While video instance segmentation provides time-consistent instance masks, results are unsatisfactory
Externí odkaz:
http://arxiv.org/abs/2311.04212
Autor:
Cynthia Al Hageh, Siobhán O’Sullivan, Andreas Henschel, Antoine Abchee, Mireille Hantouche, Nantia Iakovidou, Taly Issa, Stephanie Chacar, Moni Nader, Pierre A. Zalloua
Publikováno v:
Lipids in Health and Disease, Vol 23, Iss 1, Pp 1-11 (2024)
Abstract Background Severe coronary artery disease (CAD) represents an advanced arterial narrowing, often associated with critical complications like myocardial infarction and angina. This study aimed to comprehensively investigate determinants of se
Externí odkaz:
https://doaj.org/article/e1aa329fe8e84b218e1f9ea7b9a0905f
Autor:
McGenity, Clare, Clarke, Emily L, Jennings, Charlotte, Matthews, Gillian, Cartlidge, Caroline, Freduah-Agyemang, Henschel, Stocken, Deborah D, Treanor, Darren
Ensuring diagnostic performance of AI models before clinical use is key to the safe and successful adoption of these technologies. Studies reporting AI applied to digital pathology images for diagnostic purposes have rapidly increased in number in re
Externí odkaz:
http://arxiv.org/abs/2306.07999
Autor:
Hayashi, Soichi, Caron, Bradley A., Heinsfeld, Anibal Sólon, Vinci-Booher, Sophia, McPherson, Brent, Bullock, Daniel N., Bertò, Giulia, Niso, Guiomar, Hanekamp, Sandra, Levitas, Daniel, Ray, Kimberly, MacKenzie, Anne, Kitchell, Lindsey, Leong, Josiah K., Nascimento-Silva, Filipi, Koudoro, Serge, Willis, Hanna, Jolly, Jasleen K., Pisner, Derek, Zuidema, Taylor R., Kurzawski, Jan W., Mikellidou, Kyriaki, Bussalb, Aurore, Rorden, Christopher, Victory, Conner, Bhatia, Dheeraj, Aydogan, Dogu Baran, Yeh, Fang-Cheng F., Delogu, Franco, Guaje, Javier, Veraart, Jelle, Bollman, Steffen, Stewart, Ashley, Fischer, Jeremy, Faskowitz, Joshua, Chaumon, Maximilien, Fabrega, Ricardo, Hunt, David, McKee, Shawn, Brown, Shawn T., Heyman, Stephanie, Iacovella, Vittorio, Mejia, Amanda F., Marinazzo, Daniele, Craddock, R. Cameron, Olivetti, Emanuele, Hanson, Jamie L., Avesani, Paolo, Garyfallidis, Eleftherios, Stanzione, Dan, Carson, James, Henschel, Robert, Hancock, David Y., Stewart, Craig A., Schnyer, David, Eke, Damian O., Poldrack, Russell A., George, Nathalie, Bridge, Holly, Sani, Ilaria, Freiwald, Winrich A., Puce, Aina, Port, Nicholas L., Pestilli, Franco
Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering access to FAIR
Externí odkaz:
http://arxiv.org/abs/2306.02183
Autor:
Khachatryan, Levon, Movsisyan, Andranik, Tadevosyan, Vahram, Henschel, Roberto, Wang, Zhangyang, Navasardyan, Shant, Shi, Humphrey
Recent text-to-video generation approaches rely on computationally heavy training and require large-scale video datasets. In this paper, we introduce a new task of zero-shot text-to-video generation and propose a low-cost approach (without any traini
Externí odkaz:
http://arxiv.org/abs/2303.13439