Zobrazeno 1 - 10
of 4 000
pro vyhledávání: '"Apolinário A"'
Training deep neural networks (DNNs) using traditional backpropagation (BP) presents challenges in terms of computational complexity and energy consumption, particularly for on-device learning where computational resources are limited. Various altern
Externí odkaz:
http://arxiv.org/abs/2405.15868
Autor:
Andrés, Carlota, Apolinário, Liliana, Armesto, Néstor, Cordeiro, André, Dominguez, Fabio, Milhano, José Guilherme
The theoretical treatment of jet quenching lacks a full description of the interplay between vacuum-like emissions, usually formulated in momentum space, and medium induced ones that demand an interface with a space-time picture of the expanding medi
Externí odkaz:
http://arxiv.org/abs/2402.09482
Publikováno v:
Eur.Phys.J.C 84 (2024) 7, 672
In this manuscript, we illustrate how to use the newly proposed $\tau$ re-clustering algorithm to select jets with different degrees of quenching without biasing their initial transverse momentum spectrum. Our study is based on Z+jet simulated events
Externí odkaz:
http://arxiv.org/abs/2401.14229
Autor:
Brack, Manuel, Friedrich, Felix, Kornmeier, Katharina, Tsaban, Linoy, Schramowski, Patrick, Kersting, Kristian, Passos, Apolinário
Text-to-image diffusion models have recently received increasing interest for their astonishing ability to produce high-fidelity images from solely text inputs. Subsequent research efforts aim to exploit and apply their capabilities to real image edi
Externí odkaz:
http://arxiv.org/abs/2311.16711
Autor:
Luo, Simian, Tan, Yiqin, Patil, Suraj, Gu, Daniel, von Platen, Patrick, Passos, Apolinário, Huang, Longbo, Li, Jian, Zhao, Hang
Latent Consistency Models (LCMs) have achieved impressive performance in accelerating text-to-image generative tasks, producing high-quality images with minimal inference steps. LCMs are distilled from pre-trained latent diffusion models (LDMs), requ
Externí odkaz:
http://arxiv.org/abs/2311.05556
Autor:
Apolinário, L, Assis, P., Brogueira, P., Conceição, R., Costa, P. J., La Mura, G., Pimenta, M., Tomé, B.
The lower energy thresholds of large wide-field gamma-ray observatories are often determined by their capability to deal with the very low-energy cosmic ray background. In fact, in observatories with areas of tens or hundreds of thousands of square m
Externí odkaz:
http://arxiv.org/abs/2310.15860
Autor:
Andrés, Carlota, Apolinário, Liliana, Armesto, Néstor, Cordeiro, André, Dominguez, Fabio, Milhano, José Guilherme
While experimental studies on jet quenching have achieved a large sophistication, the theoretical description of this phenomenon still misses some important points. One of them is the interplay of vacuum-like emissions, usually formulated in momentum
Externí odkaz:
http://arxiv.org/abs/2307.08410
Over the past years, there has been a sustained effort to systematically enhance our understanding of medium-induced emissions occurring in the quark-gluon plasma, driven by the ultimate goal of advancing our comprehension of jet quenching phenomena.
Externí odkaz:
http://arxiv.org/abs/2307.06226
Autor:
Tsaban, Linoy, Passos, Apolinário
Recent large-scale text-guided diffusion models provide powerful image-generation capabilities. Currently, a significant effort is given to enable the modification of these images using text only as means to offer intuitive and versatile editing. How
Externí odkaz:
http://arxiv.org/abs/2307.00522
Autor:
Izabela Aline Gomes da Silva, José Carlos Batista Dubeux, Carla Giselly Souza, Martin Ruiz Moreno, Mércia Virgínia Ferreira dos Santos, Valéria Xavier de Oliveira Apolinário, Alexandre Carneiro Leão de Mello, Márcio Vieira da Cunha, James Pierre Muir, Mario Andrade Lira Junior
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract Introducing legumes into C4-dominated tropical pastures, may enhance their sustainability but has some pasture management constraints. One potential alternative is using arboreal legumes, but several of these species have relatively high con
Externí odkaz:
https://doaj.org/article/06ccbc0220f34bcdb748141de709af87