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Akademický článek
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Autor:
Gekkieva, S. Kh.1 (AUTHOR) gekkieva_s@mail.ru, Kerefov, M. A.2 (AUTHOR)
Publikováno v:
Journal of Mathematical Sciences. Jan2022, Vol. 260 Issue 3, p300-306. 7p.
Akademický článek
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Publikováno v:
Vestnik Samarskogo Gosudarstvennogo Tehničeskogo Universiteta. Seriâ: Fiziko-Matematičeskie Nauki, Vol 23, Iss 4, Pp 607-621 (2019)
The equations that describe a new type of wave motion arise in the course of mathematical modeling for continuous media with memory. This refers to differential equations of fractional order, which form the basis for most mathematical models describi
Externí odkaz:
https://doaj.org/article/f702043b3dcb45918c9730af6bc19913
Autor:
Guo, Ziang, Lin, Xinhao, Yagudin, Zakhar, Lykov, Artem, Wang, Yong, Li, Yanqiang, Tsetserukou, Dzmitry
Multi-modal end-to-end autonomous driving has shown promising advancements in recent work. By embedding more modalities into end-to-end networks, the system's understanding of both static and dynamic aspects of the driving environment is enhanced, th
Externí odkaz:
http://arxiv.org/abs/2409.12667
Autor:
Lykov, Artem, Cabrera, Miguel Altamirano, Konenkov, Mikhail, Serpiva, Valerii, Gbagbe, Koffivi Fid`ele, Alabbas, Ali, Fedoseev, Aleksey, Moreno, Luis, Khan, Muhammad Haris, Guo, Ziang, Tsetserukou, Dzmitry
This paper presents the concept of Industry 6.0, introducing the world's first fully automated production system that autonomously handles the entire product design and manufacturing process based on user-provided natural language descriptions. By le
Externí odkaz:
http://arxiv.org/abs/2409.10106
Autor:
Scheerer, Jan Luca, Lykov, Anton, Kayali, Moe, Fountalis, Ilias, Olteanu, Dan, Vasiloglou, Nikolaos, Suciu, Dan
We demonstrate QirK, a system for answering natural language questions on Knowledge Graphs (KG). QirK can answer structurally complex questions that are still beyond the reach of emerging Large Language Models (LLMs). It does so using a unique combin
Externí odkaz:
http://arxiv.org/abs/2408.07494
Autor:
DeCross, Matthew, Haghshenas, Reza, Liu, Minzhao, Rinaldi, Enrico, Gray, Johnnie, Alexeev, Yuri, Baldwin, Charles H., Bartolotta, John P., Bohn, Matthew, Chertkov, Eli, Cline, Julia, Colina, Jonhas, DelVento, Davide, Dreiling, Joan M., Foltz, Cameron, Gaebler, John P., Gatterman, Thomas M., Gilbreth, Christopher N., Giles, Joshua, Gresh, Dan, Hall, Alex, Hankin, Aaron, Hansen, Azure, Hewitt, Nathan, Hoffman, Ian, Holliman, Craig, Hutson, Ross B., Jacobs, Trent, Johansen, Jacob, Lee, Patricia J., Lehman, Elliot, Lucchetti, Dominic, Lykov, Danylo, Madjarov, Ivaylo S., Mathewson, Brian, Mayer, Karl, Mills, Michael, Niroula, Pradeep, Pino, Juan M., Roman, Conrad, Schecter, Michael, Siegfried, Peter E., Tiemann, Bruce G., Volin, Curtis, Walker, James, Shaydulin, Ruslan, Pistoia, Marco, Moses, Steven. A., Hayes, David, Neyenhuis, Brian, Stutz, Russell P., Foss-Feig, Michael
Empirical evidence for a gap between the computational powers of classical and quantum computers has been provided by experiments that sample the output distributions of two-dimensional quantum circuits. Many attempts to close this gap have utilized
Externí odkaz:
http://arxiv.org/abs/2406.02501
Camera, LiDAR and radar are common perception sensors for autonomous driving tasks. Robust prediction of 3D object detection is optimally based on the fusion of these sensors. To exploit their abilities wisely remains a challenge because each of thes
Externí odkaz:
http://arxiv.org/abs/2405.11682
The advent of immersive Virtual Reality applications has transformed various domains, yet their integration with advanced artificial intelligence technologies like Visual Language Models remains underexplored. This study introduces a pioneering appro
Externí odkaz:
http://arxiv.org/abs/2405.11537