Zobrazeno 1 - 10
of 11 740
pro vyhledávání: '"Romera, A."'
Autor:
Romera, Gonzalo
In this Master Thesis, we study the approximation capabilities of Neural Networks in the context of numerical resolution of elliptic PDEs and Approximation Theory. First of all, in Chapter 1, we introduce the mathematical definition of Neural Network
Externí odkaz:
http://arxiv.org/abs/2410.02814
Autor:
Millan-Romera, Jose Andres, Bavle, Hriday, Shaheer, Muhammad, Voos, Holger, Sanchez-Lopez, Jose Luis
Understanding the relationships between geometric structures and semantic concepts is crucial for building accurate models of complex environments. In indoors, certain spatial constraints, such as the relative positioning of planes, remain consistent
Externí odkaz:
http://arxiv.org/abs/2409.11972
Autor:
Martínez, E. A., Lucero, A. M., Cantero, E. D., Biškup, N., Orte, A., Sánchez, E. A., Romera, M., Nemes, N. M., Martínez, J. L., Varela, M., Grizzi, O., Bruno, F. Y.
The two-dimensional electron gas (2DEG) found in KTaO3-based interfaces has garnered attention due to its remarkable electronic properties. In this study, we investigated the conducting system embedded at the Si3N4/Al//KTO(110) heterostructure. We de
Externí odkaz:
http://arxiv.org/abs/2409.11893
Autor:
Shaheer, Muhammad, Millan-Romera, Jose Andres, Bavle, Hriday, Giberna, Marco, Sanchez-Lopez, Jose Luis, Civera, Javier, Voos, Holger
Having prior knowledge of an environment boosts the localization and mapping accuracy of robots. Several approaches in the literature have utilized architectural plans in this regard. However, almost all of them overlook the deviations between actual
Externí odkaz:
http://arxiv.org/abs/2408.01737
Autor:
Lopez, A., Costa, D., Bohnert, T., Freitas, P. P., Ferreira, R., Barbero, I., Camarero, J., Leon, C., Grollier, J., Romera, M.
A promising branch of neuromorphic computing aims to perform cognitive operations in hardware leveraging the physics of efficient and well-established nano-devices. In this work, we present a reconfigurable classifier based on a network of electrical
Externí odkaz:
http://arxiv.org/abs/2407.06768
Nonrelativistic Quantum Chromodynamics (NRQCD) breaks down in the region of low transverse momentum, where the transverse momentum of the produced quarkonium state is sensitive to multiple scattering with the incoming hadron and to soft gluon radiati
Externí odkaz:
http://arxiv.org/abs/2407.04793
Autor:
Vázquez-Lema, David, Mosqueira-Rey, Eduardo, Hernández-Pereira, Elena, Fernández-Lozano, Carlos, Seara-Romera, Fernando, Pombo-Otero, Jorge
This paper explores the application of Human-in-the-Loop (HITL) strategies in training machine learning models in the medical domain. In this case a doctor-in-the-loop approach is proposed to leverage human expertise in dealing with large and complex
Externí odkaz:
http://arxiv.org/abs/2403.20112
Autor:
Ruiz, Francisco J. R., Laakkonen, Tuomas, Bausch, Johannes, Balog, Matej, Barekatain, Mohammadamin, Heras, Francisco J. H., Novikov, Alexander, Fitzpatrick, Nathan, Romera-Paredes, Bernardino, van de Wetering, John, Fawzi, Alhussein, Meichanetzidis, Konstantinos, Kohli, Pushmeet
A key challenge in realizing fault-tolerant quantum computers is circuit optimization. Focusing on the most expensive gates in fault-tolerant quantum computation (namely, the T gates), we address the problem of T-count optimization, i.e., minimizing
Externí odkaz:
http://arxiv.org/abs/2402.14396
Autor:
Perez-Diaz, Jose-Luis, Garcia-Prada, Juan Carlos, Diez-Jimenez, Efren, a, Ignacio Valiente-Blanco, Sander, Berit, Timm, Lauri, Sanchez-Garcia-Casarrubios, Juan, Serrano, Javier, Romera, Fernando, Argelaguet-Vilaseca, Heribert, Gonzalez-de-Maria, David
A non-contact linear slider based on stable superconducting magnetic levitation with a long permanent magnet as a slider and two fixed superconducting disks which define the slide way has been designed, built and tested. The slider can be moved stabl
Externí odkaz:
http://arxiv.org/abs/2402.00557
Publikováno v:
26th IEEE International Conference on Intelligent Transportation Systems ITSC 2023
Pedestrian intention prediction is crucial for autonomous driving. In particular, knowing if pedestrians are going to cross in front of the ego-vehicle is core to performing safe and comfortable maneuvers. Creating accurate and fast models that predi
Externí odkaz:
http://arxiv.org/abs/2401.06757