Zobrazeno 1 - 10
of 10 058
pro vyhledávání: '"A. Almagro"'
Autor:
Ding, Tong, Wagner, Sophia J., Song, Andrew H., Chen, Richard J., Lu, Ming Y., Zhang, Andrew, Vaidya, Anurag J., Jaume, Guillaume, Shaban, Muhammad, Kim, Ahrong, Williamson, Drew F. K., Chen, Bowen, Almagro-Perez, Cristina, Doucet, Paul, Sahai, Sharifa, Chen, Chengkuan, Komura, Daisuke, Kawabe, Akihiro, Ishikawa, Shumpei, Gerber, Georg, Peng, Tingying, Le, Long Phi, Mahmood, Faisal
The field of computational pathology has been transformed with recent advances in foundation models that encode histopathology region-of-interests (ROIs) into versatile and transferable feature representations via self-supervised learning (SSL). Howe
Externí odkaz:
http://arxiv.org/abs/2411.19666
Publikováno v:
Hydrology and Earth System Sciences, Vol 25, Pp 3105-3135 (2021)
In this paper, we present the Catchments Attributes for Brazil (CABra), which is a large-sample dataset for Brazilian catchments that includes long-term data (30 years) for 735 catchments in eight main catchment attribute classes (climate, streamflow
Externí odkaz:
https://doaj.org/article/103f28bff1c54bd8b671ec21d0f8e28f
Autor:
Jafrasteh, Bahram, Lubian-Lopez, Simon Pedro, Trimarco, Emiliano, Ruiz, Macarena Roman, Barrios, Carmen Rodriguez, Almagro, Yolanda Marin, Benavente-Fernandez, Isabel
In this study, we introduce MGA-Net, a novel mask-guided attention neural network, which extends the U-net model for precision neonatal brain imaging. MGA-Net is designed to extract the brain from other structures and reconstruct high-quality brain i
Externí odkaz:
http://arxiv.org/abs/2406.17709
Autor:
Jaume, Guillaume, Doucet, Paul, Song, Andrew H., Lu, Ming Y., Almagro-Pérez, Cristina, Wagner, Sophia J., Vaidya, Anurag J., Chen, Richard J., Williamson, Drew F. K., Kim, Ahrong, Mahmood, Faisal
Spatial transcriptomics enables interrogating the molecular composition of tissue with ever-increasing resolution and sensitivity. However, costs, rapidly evolving technology, and lack of standards have constrained computational methods in ST to narr
Externí odkaz:
http://arxiv.org/abs/2406.16192
Autor:
Florensa, Alfred Ferrer, Armenteros, Jose Juan Almagro, Nielsen, Henrik, Aarestrup, Frank Møller, Clausen, Philip Thomas Lanken Conradsen
Publikováno v:
NAR Genomics and Bioinformatics, Volume 6, Issue 3, September 2024
The use of deep learning models in computational biology has increased massively in recent years, and it is expected to continue with the current advances in the fields such as Natural Language Processing. These models, although able to draw complex
Externí odkaz:
http://arxiv.org/abs/2402.14482
Autor:
Celledoni, Elena, Çokaj, Ergys, Leone, Andrea, Leyendecker, Sigrid, Murari, Davide, Owren, Brynjulf, de Almagro, Rodrigo T. Sato Martín, Stavole, Martina
Euler's elastica is a classical model of flexible slender structures, relevant in many industrial applications. Static equilibrium equations can be derived via a variational principle. The accurate approximation of solutions of this problem can be ch
Externí odkaz:
http://arxiv.org/abs/2312.00644
Autor:
A. Almagro
Publikováno v:
Informes de la Construccion, Vol 70, Iss 550, Pp e248-e248 (2018)
Se analiza en este estudio el comportamiento del agua en las albercas que existieron dentro de la sala del pabellón occidental del patio central del palacio de al-Badi’ de Marrakech, realizado a través de un modelo real a escala reducida que repr
Externí odkaz:
https://doaj.org/article/a86289c1bc5f473aa31107c1a6abe550
Autor:
Almagro, Manuel
Publikováno v:
Theoria: An International Journal for Theory, History and Foundations of Science, 2024 Jan 01. 39(1), 23-42.
Externí odkaz:
https://www.jstor.org/stable/27304492
Autor:
Leyendecker, Sigrid, Maslovskaya, Sofya, Ober-Blobaum, Sina, de Almagro, Rodrigo T. Sato Martin, Szemenyei, Flora Orsolya
In this work, we consider optimal control problems for mechanical systems on vector spaces with fixed initial and free final state and a quadratic Lagrange term. Specifically, the dynamics is described by a second order ODE containing an affine contr
Externí odkaz:
http://arxiv.org/abs/2307.13402
Textual noise, such as typos or abbreviations, is a well-known issue that penalizes vanilla Transformers for most downstream tasks. We show that this is also the case for sentence similarity, a fundamental task in multiple domains, e.g. matching, ret
Externí odkaz:
http://arxiv.org/abs/2307.02912