Zobrazeno 1 - 10
of 10 138
pro vyhledávání: '"P. Latorre"'
Autor:
Torres-Latorre, Clara
We obtain boundary nondegeneracy and regularity estimates for harmonic functions in $C^1$ domains, providing an explicit modulus of continuity. Our results extend the classical Hopf-Oleinik lemma and boundary Lipschitz regularity for domains with $C^
Externí odkaz:
http://arxiv.org/abs/2410.15782
Publikováno v:
Applied Soft Computing, vol. 148, p. 110914, Nov. 2023
Identifying client needs to provide optimal services is crucial in tourist destination management. The events held in tourist destinations may help to meet those needs and thus contribute to tourist satisfaction. As with product management, the creat
Externí odkaz:
http://arxiv.org/abs/2410.19741
Publikováno v:
Mathematics, vol. 10, no. 9, Art. no. 9, Jan. 2022
The military environment generates a large amount of data of great importance, which makes necessary the use of machine learning for its processing. Its ability to learn and predict possible scenarios by analyzing the huge volume of information gener
Externí odkaz:
http://arxiv.org/abs/2410.17272
Publikováno v:
Swarm and Evolutionary Computation, vol. 75, p. 101176, Dec. 2022
Heuristic optimisation algorithms explore the search space by sampling solutions, evaluating their fitness, and biasing the search in the direction of promising solutions. However, in many cases, this fitness function involves executing expensive com
Externí odkaz:
http://arxiv.org/abs/2410.03409
Publikováno v:
Expert Systems with Applications, vol. 183, p. 115443, Nov. 2021
Background Analyzing images to accurately estimate the number of different cell types in the brain using automatic methods is a major objective in neuroscience. The automatic and selective detection and segmentation of neurons would be an important s
Externí odkaz:
http://arxiv.org/abs/2410.03248
Autor:
Osaba, Eneko, Villar-Rodriguez, Esther, Del Ser, Javier, Nebro, Antonio J., Molina, Daniel, LaTorre, Antonio, Suganthan, Ponnuthurai N., Coello, Carlos A. Coello, Herrera, Francisco
Publikováno v:
Swarm and Evolutionary Computation, vol. 64, p. 100888, Jul. 2021
In the last few years, the formulation of real-world optimization problems and their efficient solution via metaheuristic algorithms has been a catalyst for a myriad of research studies. In spite of decades of historical advancements on the design an
Externí odkaz:
http://arxiv.org/abs/2410.03205
Autor:
Pasquale, Andrea, Pedicillo, Edoardo, Cereijo, Juan, Ramos-Calderer, Sergi, Candido, Alessandro, Palazzo, Gabriele, Carobene, Rodolfo, Gobbo, Marco, Efthymiou, Stavros, Tan, Yuanzheng Paul, Roth, Ingo, Robbiati, Matteo, Wilkens, Jadwiga, Orgaz-Fuertes, Alvaro, Fuentes-Ruiz, David, Giachero, Andrea, Brito, Frederico, Latorre, José Ignacio, Carrazza, Stefano
Calibration of quantum devices is fundamental to successfully deploy quantum algorithms on current available quantum hardware. We present Qibocal, an open-source software library to perform calibration and characterization of superconducting quantum
Externí odkaz:
http://arxiv.org/abs/2410.00101
Autor:
LaTorre, Antonio, Kwong, Man Ting, García-Grajales, Julián A., Shi, Riyi, Jérusalem, Antoine, Peña, José-María
Publikováno v:
Journal of Computational Science, vol. 39, p. 101053, Jan. 2020
Neuronal damage, in the form of both brain and spinal cord injuries, is one of the major causes of disability and death in young adults worldwide. One way to assess the direct damage occurring after a mechanical insult is the simulation of the neuron
Externí odkaz:
http://arxiv.org/abs/2409.12567
The main purpose of this work is the derivation of a functional partial differential equation (FPDE) for the calculations of equity-linked insurance policies, where the payment stream may depend on the whole past history of the financial asset. To th
Externí odkaz:
http://arxiv.org/abs/2409.00780
We explore deep generative models to generate case-based explanations in a medical federated learning setting. Explaining AI model decisions through case-based interpretability is paramount to increasing trust and allowing widespread adoption of AI i
Externí odkaz:
http://arxiv.org/abs/2408.13626