Zobrazeno 1 - 10
of 354 427
pro vyhledávání: '"Jesus, A."'
Autor:
Angeloudi, Eirini, Huertas-Company, Marc, Falcón-Barroso, Jesús, Sarmiento, Regina, Walo-Martín, Daniel, Pillepich, Annalisa, Ferrero, Jesús Vega
Galaxies grow through star formation (in-situ) and accretion (ex-situ) of other galaxies. Reconstructing the relative contribution of these two growth channels is crucial for constraining the processes of galaxy formation in a cosmological context. I
Externí odkaz:
http://arxiv.org/abs/2410.24069
Autor:
García-Benito, Rubén, Jiménez, Andoni, Sánchez-Menguiano, Laura, Ruiz-Lara, Tomás, Puertas, Salvador Duarte, Domínguez-Gómez, Jesús, Bidaran, Bahar, Torres-Ríos, Gloria, Argudo-Fernández, María, Espada, Daniel, Pérez, Isabel, Verley, Simon, Conrado, Ana M., Florido, Estrella, Rodríguez, Mónica I., Zurita, Almudena, Alcázar-Laynez, Manuel, De Daniloff, Simon B., Lisenfeld, Ute, van de Weygaert, Rien, Courtois, Hélène M., Falcón-Barroso, Jesús, Ferré-Mateu, Anna, Galbany, Lluís, Delgado, Rosa M. González, del Moral-Castro, Ignacio, Peletier, Reynier F., Román, Javier, Sánchez, Sebastián F., Sánchez-Alarcón, Pablo M., Sánchez-Blázquez, Patricia, Villalba-González, Pedro, Azzaro, Marco, Blazek, Martín, Fernández, Alba, Gallego, Julia, Góngora, Samuel, Guijarro, Ana, de Guindos, Enrique, Hermelo, Israel, Hernández, Ricardo, de Juan, Enrique, Linares, José Ignacio Vico
The Calar Alto Void Integral-field Treasury surveY (CAVITY) is a legacy project aimed at characterising the population of galaxies inhabiting voids, which are the most under-dense regions of the cosmic web, located in the Local Universe. This paper d
Externí odkaz:
http://arxiv.org/abs/2410.08265
Autor:
Domínguez, Francisco, Yousaf, David, Berrocal, Joaquín, Gutiérrez, Manuel Jesús, Sánchez, Jesús, Block, Michael, Rodríguez, Daniel
Single-ion mass identification is important for atomic and nuclear physics experiments on ions produced with low yields. Cooling the ion to ultra-low temperatures by interacting with a laser-cooled ion will enhance the precision of the measurements.
Externí odkaz:
http://arxiv.org/abs/2409.17883
The challenges in dense ultra-reliable low-latency communication networks to deliver the required service to multiple devices are addressed by three main technologies: multiple antennas at the base station (MISO), rate splitting multiple access (RSMA
Externí odkaz:
http://arxiv.org/abs/2411.04581
This paper presents the winning solution of task 1 and the third-placed solution of task 3 of the BraTS challenge. The use of automated tools in clinical practice has increased due to the development of more and more sophisticated and reliable algori
Externí odkaz:
http://arxiv.org/abs/2411.04632
Autor:
Connell, Chris, Dai, Xianzhe, Núñez-Zimbrón, Jesús, Perales, Raquel, Suárez-Serrato, Pablo, Wei, Guofang
We develop the barycenter technique of Besson--Courtois--Gallot so that it can be applied on RCD metric measure spaces. Given a continuous map $f$ from a non-collapsed RCD$(-(N-1),N)$ space $X$ without boundary to a locally symmetric $N$-manifold we
Externí odkaz:
http://arxiv.org/abs/2411.04327
Autor:
Talbot, William, Nubert, Julian, Tuna, Turcan, Cadena, Cesar, Dümbgen, Frederike, Tordesillas, Jesus, Barfoot, Timothy D., Hutter, Marco
Accurate, efficient, and robust state estimation is more important than ever in robotics as the variety of platforms and complexity of tasks continue to grow. Historically, discrete-time filters and smoothers have been the dominant approach, in which
Externí odkaz:
http://arxiv.org/abs/2411.03951
Autor:
Bagajo, Joshua, Schwarke, Clemens, Klemm, Victor, Georgiev, Ignat, Sleiman, Jean-Pierre, Tordesillas, Jesus, Garg, Animesh, Hutter, Marco
Differentiable simulators provide analytic gradients, enabling more sample-efficient learning algorithms and paving the way for data intensive learning tasks such as learning from images. In this work, we demonstrate that locomotion policies trained
Externí odkaz:
http://arxiv.org/abs/2411.02189
Autor:
Calvo, Alvaro, Capitan, Jesus
We present a framework for Multi-Robot Task Allocation (MRTA) in heterogeneous teams performing long-endurance missions in dynamic scenarios. Given the limited battery of robots, especially in the case of aerial vehicles, we allow for robot recharges
Externí odkaz:
http://arxiv.org/abs/2411.02062
The Certainty Ratio $C_\rho$: a novel metric for assessing the reliability of classifier predictions
Autor:
Aguilar-Ruiz, Jesus S.
Evaluating the performance of classifiers is critical in machine learning, particularly in high-stakes applications where the reliability of predictions can significantly impact decision-making. Traditional performance measures, such as accuracy and
Externí odkaz:
http://arxiv.org/abs/2411.01973