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pro vyhledávání: '"A. Gos"'
Hypergraphs are characterized by complex topological structure, representing higher-order interactions among multiple entities through hyperedges. Lately, hypergraph-based deep learning methods to learn informative data representations for the proble
Externí odkaz:
http://arxiv.org/abs/2402.07309
Recent advances in the development of pre-trained Spanish language models has led to significant progress in many Natural Language Processing (NLP) tasks, such as question answering. However, the lack of efficient models imposes a barrier for the ado
Externí odkaz:
http://arxiv.org/abs/2312.04193
In recent years, the task of text-to-SQL translation, which converts natural language questions into executable SQL queries, has gained significant attention for its potential to democratize data access. Despite its promise, challenges such as adapti
Externí odkaz:
http://arxiv.org/abs/2310.18376
Fact verification aims to verify a claim using evidence from a trustworthy knowledge base. To address this challenge, algorithms must produce features for every claim that are both semantically meaningful, and compact enough to find a semantic alignm
Externí odkaz:
http://arxiv.org/abs/2309.16540
Akademický článek
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Autor:
Gos, Anna1 (AUTHOR), Steiner, Johann1 (AUTHOR), Trübner, Kurt2 (AUTHOR), Ungewickell, Jonas1 (AUTHOR), Mawrin, Christian3 (AUTHOR), Karnecki, Karol4 (AUTHOR), Kaliszan, Michał4 (AUTHOR), Gos, Tomasz1,4 (AUTHOR) gost@gumed.edu.pl
Publikováno v:
European Archives of Psychiatry & Clinical Neuroscience. Mar2024, Vol. 274 Issue 2, p445-452. 8p.
Autor:
Gos, María Laura, Venturini, María Cecilia, De Felice, Lorena, Dellarupe, Andrea, Rambeaud, Magdalena, Pardini, Lais, Campero, Lucía María, Bernstein, Mariana, Bacigalupe, Diana, Basso, Walter, Moré, Gastón, Unzaga, Juan Manuel
Publikováno v:
In Veterinary Parasitology August 2024 330
Autor:
Raj-Koziak, Danuta, Gos, Elżbieta, Porowski, Marek, Skarzynski, Piotr Henryk, Skarzynski, Henryk
Publikováno v:
In International Journal of Pediatric Otorhinolaryngology July 2024 182
Autor:
Pion-Tonachini, Luca, Bouchard, Kristofer, Martin, Hector Garcia, Peisert, Sean, Holtz, W. Bradley, Aswani, Anil, Dwivedi, Dipankar, Wainwright, Haruko, Pilania, Ghanshyam, Nachman, Benjamin, Marrone, Babetta L., Falco, Nicola, Prabhat, Arnold, Daniel, Wolf-Yadlin, Alejandro, Powers, Sarah, Climer, Sharlee, Jackson, Quinn, Carlson, Ty, Sohn, Michael, Zwart, Petrus, Kumar, Neeraj, Justice, Amy, Tomlin, Claire, Jacobson, Daniel, Micklem, Gos, Gkoutos, Georgios V., Bickel, Peter J., Cazier, Jean-Baptiste, Müller, Juliane, Webb-Robertson, Bobbie-Jo, Stevens, Rick, Anderson, Mark, Kreutz-Delgado, Ken, Mahoney, Michael W., Brown, James B.
We outline emerging opportunities and challenges to enhance the utility of AI for scientific discovery. The distinct goals of AI for industry versus the goals of AI for science create tension between identifying patterns in data versus discovering pa
Externí odkaz:
http://arxiv.org/abs/2111.13786
The number of databases as well as their size and complexity is increasing. This creates a barrier to use especially for non-experts, who have to come to grips with the nature of the data, the way it has been represented in the database, and the spec
Externí odkaz:
http://arxiv.org/abs/2104.07010