Zobrazeno 1 - 10
of 1 681
pro vyhledávání: '"Paliouras A"'
Autor:
Kompostiotis, Dimitris, Vordonis, Dimitris, Paliouras, Vassilis, Alexandropoulos, George C., Grec, Florin
A Reconfigurable Intelligent Surface (RIS) can significantly enhance network positioning and mapping, acting as an additional anchor point in the reference system and improving signal strength and measurement diversity through the generation of favor
Externí odkaz:
http://arxiv.org/abs/2411.09440
In this work, we generalize the ideas of Kaiming initialization to Graph Neural Networks (GNNs) and propose a new scheme (G-Init) that reduces oversmoothing, leading to very good results in node and graph classification tasks. GNNs are commonly initi
Externí odkaz:
http://arxiv.org/abs/2410.23830
In this work we investigate an observation made by Kipf \& Welling, who suggested that untrained GCNs can generate meaningful node embeddings. In particular, we investigate the effect of training only a single layer of a GCN, while keeping the rest o
Externí odkaz:
http://arxiv.org/abs/2410.13416
Autor:
Zachariou A, Filiponi M, Kaltsas A, Dimitriadis F, Champilomatis I, Paliouras A, Tsounapi P, Mamoulakis C, Takenaka A, Sofikitis N
Publikováno v:
Clinical Interventions in Aging, Vol Volume 16, Pp 291-299 (2021)
Athanasios Zachariou,1,2 Maria Filiponi,2 Aris Kaltsas,1,2 Fotios Dimitriadis,3 Ioannis Champilomatis,1 Athanasios Paliouras,1 Panagiota Tsounapi,4 Charalampos Mamoulakis,5 Atsushi Takenaka,4 Nikolaos Sofikitis1 1Urology Department, School of Medicin
Externí odkaz:
https://doaj.org/article/fd7bbfbb33bc4dd7b6e362c3e572ca51
Autor:
Krithara, Anastasia, Aisopos, Fotis, Rentoumi, Vassiliki, Nentidis, Anastasios, Bougatiotis, Konstantinos, Vidal, Maria-Esther, Menasalvas, Ernestina, Rodriguez-Gonzalez, Alejandro, Samaras, Eleftherios G., Garrard, Peter, Torrente, Maria, Pulla, Mariano Provencio, Dimakopoulos, Nikos, Mauricio, Rui, De Argila, Jordi Rambla, Tartaglia, Gian Gaetano, Paliouras, George
Publikováno v:
2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS), Cordoba, Spain, 2019, pp. 106-111
The vision of IASIS project is to turn the wave of big biomedical data heading our way into actionable knowledge for decision makers. This is achieved by integrating data from disparate sources, including genomics, electronic health records and bibli
Externí odkaz:
http://arxiv.org/abs/2407.06748
We present a system for Complex Event Recognition (CER) based on automata. While multiple such systems have been described in the literature, they typically suffer from a lack of clear and denotational semantics, a limitation which often leads to con
Externí odkaz:
http://arxiv.org/abs/2407.02884
Autor:
Yinan Xiao, Yaru Ren, Wenteng Hu, Athanasios R. Paliouras, Wenyang Zhang, Linghui Zhong, Kaixin Yang, Li Su, Peng Wang, Yonghong Li, Minjie Ma, Lei Shi
Publikováno v:
Cell Death Discovery, Vol 10, Iss 1, Pp 1-15 (2024)
Abstract Long non-coding RNAs (lncRNAs) are typically described as RNA transcripts exceeding 200 nucleotides in length, which do not code for proteins. Recent advancements in technology, including ribosome RNA sequencing and ribosome nascent-chain co
Externí odkaz:
https://doaj.org/article/14e5e082aa0d4c32b39edbfb7ff87439
Autor:
Nentidis, Anastasios, Katsimpras, Georgios, Krithara, Anastasia, López, Salvador Lima, Farré-Maduell, Eulália, Gasco, Luis, Krallinger, Martin, Paliouras, Georgios
Publikováno v:
CLEF 2023. Lecture Notes in Computer Science, vol 14163. Springer, Cham
This is an overview of the eleventh edition of the BioASQ challenge in the context of the Conference and Labs of the Evaluation Forum (CLEF) 2023. BioASQ is a series of international challenges promoting advances in large-scale biomedical semantic in
Externí odkaz:
http://arxiv.org/abs/2307.05131
Autor:
Zavitsanos, Elias, Mavroeidis, Dimitris, Bougiatiotis, Konstantinos, Spyropoulou, Eirini, Loukas, Lefteris, Paliouras, Georgios
Publikováno v:
Proceedings of the Second ACM International Conference on AI in Finance, no 34, 2021
In this work, we examine the evaluation process for the task of detecting financial reports with a high risk of containing a misstatement. This task is often referred to, in the literature, as ``misstatement detection in financial reports''. We provi
Externí odkaz:
http://arxiv.org/abs/2305.17457
Most phenomena related to biomedical tasks are inherently complex, and in many cases, are expressed as signals on biomedical Knowledge Graphs (KGs). In this work, we introduce the use of a new representation framework, the Prime Adjacency Matrix (PAM
Externí odkaz:
http://arxiv.org/abs/2305.10467