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pro vyhledávání: '"RODRÍGUEZ, ÁNGEL"'
Autor:
Laura Sanz-Simón
Publikováno v:
Pragmalingüística, Iss 30 (2022)
Externí odkaz:
https://doaj.org/article/404bc0dc25444cae955f8df4f6d3d8d6
Autor:
Solano-Carrillo, Edgardo, Sattler, Felix, Alex, Antje, Klein, Alexander, Costa, Bruno Pereira, Rodriguez, Angel Bueno, Stoppe, Jannis
The tracking-by-detection paradigm is the mainstream in multi-object tracking, associating tracks to the predictions of an object detector. Although exhibiting uncertainty through a confidence score, these predictions do not capture the entire variab
Externí odkaz:
http://arxiv.org/abs/2408.17098
Publikováno v:
Pragmalingüística, Iss 28 (2020)
Se trata de una reseña de Cervera Rodríguez, Ángel (2019): Cómo elaborar trabajos académicos y científicos (TFG, TFM, tesis y artículos).
Externí odkaz:
https://doaj.org/article/06bc3854556c48c2afc6a131a65c29af
Akademický článek
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Autor:
Yue Cheng
Publikováno v:
Oralia: análisis del discurso oral. 25:193-198
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4cd15e782bb1958f049a613d15a7f224
https://doi.org/10.25115/oralia.v25i2.8350
https://doi.org/10.25115/oralia.v25i2.8350
Autor:
Rodriguez, Angel Bueno, Sattler, Felix, Prada, Maximilian Perez, Stephan, Maurice, Barnes, Sarah
The correctness and precision of particle physics simulation software, such as Geant4, is expected to yield results that closely align with real-world observations or well-established theoretical predictions. Notably, the accuracy of these simulated
Externí odkaz:
http://arxiv.org/abs/2311.06327
Autor:
Roychowdhury, Sohini, Alvarez, Andres, Moore, Brian, Krema, Marko, Gelpi, Maria Paz, Rodriguez, Federico Martin, Rodriguez, Angel, Cabrejas, Jose Ramon, Serrano, Pablo Martinez, Agrawal, Punit, Mukherjee, Arijit
Large Language Models (LLMs) have been applied to build several automation and personalized question-answering prototypes so far. However, scaling such prototypes to robust products with minimized hallucinations or fake responses still remains an ope
Externí odkaz:
http://arxiv.org/abs/2311.07592
Autor:
Solano-Carrillo, Edgardo, Rodriguez, Angel Bueno, Carrillo-Perez, Borja, Steiniger, Yannik, Stoppe, Jannis
Generative adversarial networks (GANs) are successfully used for image synthesis but are known to face instability during training. In contrast, probabilistic diffusion models (DMs) are stable and generate high-quality images, at the cost of an expen
Externí odkaz:
http://arxiv.org/abs/2304.09024