Zobrazeno 1 - 10
of 11 235
pro vyhledávání: '"P. A. Petrova"'
Autor:
P. A. Petrova, N. I. Konovalova, A. Y. Boyarintseva, D. M. Danilenko, A. D. Vasilieva, T. N. Shelepanova, A. V. Prokopets, M. Y. Eropkin
Publikováno v:
Эпидемиология и вакцинопрофилактика, Vol 23, Iss 3, Pp 88-97 (2024)
Relevance. The improvement of the surveillance of evolution of influenza viruses and the refinement of the capacity of prognostics of their evolutionary tendencies would lead to the better understanding and control on influenza epidemics. Aim. Establ
Externí odkaz:
https://doaj.org/article/fc3dee5e103f453fbced110d054fc54e
Autor:
Florez-Revuelta, Francisco, Ake-Kob, Alin, Climent-Perez, Pau, Coelho, Paulo, Colonna, Liane, Dahabiyeh, Laila, Dantas, Carina, Dogru-Huzmeli, Esra, Ekenel, Hazim Kemal, Jevremovic, Aleksandar, Hosseini-Kivanani, Nina, Ilgaz, Aysegul, Jovanovic, Mladjan, Klimczuk, Andrzej, Kuźmicz, Maksymilian M., Lameski, Petre, Luna, Ferlanda, Machado, Natália, Mujirishvili, Tamara, Pajalic, Zada, Petrova, Galidiya, Puaschitz, Nathalie G. S., Santofimia, Maria Jose, Solanas, Agusti, van Staalduinen, Wilhelmina, Yazici, Ziya Ata
This booklet on Active Assisted Living (AAL) technologies has been created as part of the GoodBrother COST Action, which has run from 2020 to 2024. COST Actions are European research programs that promote collaboration across borders, uniting researc
Externí odkaz:
http://arxiv.org/abs/2410.16733
Autor:
Paeleke, Leonard, Keshtiarast, Navid, Seehofer, Paul, Bless, Roland, Karl, Holger, Petrova, Marina, Zitterbart, Martina
6G networks will be highly dynamic, re-configurable, and resilient. To enable and support such features, employing AI has been suggested. Integrating AIin networks will likely require distributed AI deployments with resilient connectivity, e.g., for
Externí odkaz:
http://arxiv.org/abs/2410.11565
Autor:
Kvanchiani, Karina, Surovtsev, Petr, Nagaev, Alexander, Petrova, Elizaveta, Kapitanov, Alexander
This paper investigates the recognition of the Russian fingerspelling alphabet, also known as the Russian Sign Language (RSL) dactyl. Dactyl is a component of sign languages where distinct hand movements represent individual letters of a written lang
Externí odkaz:
http://arxiv.org/abs/2410.08675
In his study of graph codes, Alon introduced the concept of the odd-Ramsey number of a family of graphs $\mathcal{H}$ in $K_n$, defined as the minimum number of colours needed to colour the edges of $K_n$ so that every copy of a graph $H\in \mathcal{
Externí odkaz:
http://arxiv.org/abs/2410.05887
Autor:
Janiak, Jett, Karwowski, Jacek, Mangat, Chatrik Singh, Giglemiani, Giorgi, Petrova, Nora, Heimersheim, Stefan
We identify stable regions in the residual stream of Transformers, where the model's output remains insensitive to small activation changes, but exhibits high sensitivity at region boundaries. These regions emerge during training and become more defi
Externí odkaz:
http://arxiv.org/abs/2409.17113
Sparse Auto-Encoders (SAEs) are commonly employed in mechanistic interpretability to decompose the residual stream into monosemantic SAE latents. Recent work demonstrates that perturbing a model's activations at an early layer results in a step-funct
Externí odkaz:
http://arxiv.org/abs/2409.15019
Publikováno v:
Инфекция и иммунитет, Vol 11, Iss 1, Pp 191-196 (2021)
Despite the success in prevention and therapy, influenza remains a mass disease with mortality rate up to 0.01—0.2% worldwide.Purpose. Conducting clinical and laboratory analysis of influenza infection cases and evaluating their etiological signifi
Externí odkaz:
https://doaj.org/article/49ed265ac0de4141a25323adc4f53f08
Cooperative multi-monostatic sensing enables accurate positioning of passive targets by combining the sensed environment of multiple base stations (BS). In this work, we propose a novel fusion algorithm that optimally finds the weight to combine the
Externí odkaz:
http://arxiv.org/abs/2408.16464
Wireless MAC Protocol Synthesis and Optimization with Multi-Agent Distributed Reinforcement Learning
In this letter, we propose a novel Multi-Agent Deep Reinforcement Learning (MADRL) framework for Medium Access Control (MAC) protocol design. Unlike centralized approaches, which rely on a single entity for decision-making, MADRL empowers individual
Externí odkaz:
http://arxiv.org/abs/2408.05884