Zobrazeno 1 - 10
of 3 007
pro vyhledávání: '"Almagro, P"'
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:
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
A new procedure to construct symplectic methods for constrained mechanical systems is developed in this paper. The definition of a map coming from the notion of retraction maps allows to adapt the continuous problem to the discretization rule rather
Externí odkaz:
http://arxiv.org/abs/2306.06786
Autor:
Jacob L. Steenwyk, Sonja Knowles, Rafael W. Bastos, Charu Balamurugan, David Rinker, Matthew E. Mead, Christopher D. Roberts, Huzefa A. Raja, Yuanning Li, Ana Cristina Colabardini, Patrícia Alves de Castro, Thaila Fernanda dos Reis, Adiyantara Gumilang, María Almagro-Molto, Alexandre Alanio, Dea Garcia-Hermoso, Endrews Delbaje, Laís Pontes, Camila Figueiredo Pinzan, Angélica Zaninelli Schreiber, David Canóvas, Rafael Sanchez Luperini, Katrien Lagrou, Egídio Torrado, Fernando Rodrigues, Nicholas H. Oberlies, Xiaofan Zhou, Gustavo H. Goldman, Antonis Rokas
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-16 (2024)
Abstract Cryptic fungal pathogens pose disease management challenges due to their morphological resemblance to known pathogens. Here, we investigated the genomes and phenotypes of 53 globally distributed isolates of Aspergillus section Nidulantes fun
Externí odkaz:
https://doaj.org/article/5b9dafe24b2b40d18c7832764b5d79b9
Autor:
González-Almagro, Germán, Peralta, Daniel, De Poorter, Eli, Cano, José-Ramón, García, Salvador
Clustering is a well-known unsupervised machine learning approach capable of automatically grouping discrete sets of instances with similar characteristics. Constrained clustering is a semi-supervised extension to this process that can be used when e
Externí odkaz:
http://arxiv.org/abs/2303.00522
Autor:
González-Almagro, Germán, Suárez, Juan Luis, Sánchez-Bermejo, Pablo, Cano, José-Ramón, García, Salvador
This study addresses the problem of performing clustering in the presence of two types of background knowledge: pairwise constraints and monotonicity constraints. To achieve this, the formal framework to perform clustering under monotonicity constrai
Externí odkaz:
http://arxiv.org/abs/2302.14060