Zobrazeno 1 - 10
of 16 206
pro vyhledávání: '"Lemus A"'
Autor:
Tavera-Vázquez, Antonio, Montalvan-Sorrosa, Danai, Perez-Lemus, Gustavo, Rodriguez-Lopez, Otilio E., Martinez-Gonzalez, Jose A., Manoharan, Vinothan N., de Pablo, Juan J.
Motile liquid crystal (LC) colloids show peculiar behavior due to the high sensitivity to external stimuli driven by the LC elastic and surface effects. However, few studies focus on harnessing the LC phase transitions to propel colloidal inclusions
Externí odkaz:
http://arxiv.org/abs/2409.04912
Autor:
Yeddulapalli, Hemanth Sai, Alarcon, Mauro Lemus, Roy, Upasana, Neupane, Roshan Lal, Gafurov, Durbek, Mounesan, Motahare, Debroy, Saptarshi, Calyam, Prasad
Volunteer Edge-Cloud (VEC) computing has a significant potential to support scientific workflows in user communities contributing volunteer edge nodes. However, managing heterogeneous and intermittent resources to support machine/deep learning (ML/DL
Externí odkaz:
http://arxiv.org/abs/2409.03057
Machine-learned interatomic potentials (MILPs) are rapidly gaining interest for molecular modeling, as they provide a balance between quantum-mechanical level descriptions of atomic interactions and reasonable computational efficiency. However, quest
Externí odkaz:
http://arxiv.org/abs/2408.16157
Autor:
Ana, Díaz-Muñoz, A., Cruz-Lemus José, Moisés, Rodríguez, Mario, Piattini, Teresa, Baldassarre Maria
In the context of quantum-classical hybrid computing, evaluating analysability, which is the ease of understanding and modifying software, presents significant challenges due to the complexity and novelty of quantum algorithms. Although advances have
Externí odkaz:
http://arxiv.org/abs/2408.01105
In recent times, Volunteer Edge-Cloud (VEC) has gained traction as a cost-effective, community computing paradigm to support data-intensive scientific workflows. However, due to the highly distributed and heterogeneous nature of VEC resources, centra
Externí odkaz:
http://arxiv.org/abs/2407.01428
Autor:
Qayyum, Abdul, Mazher, Moona, Lee, Angela, Solis-Lemus, Jose A, Razzak, Imran, Niederer, Steven A
Unlike Right Atrium (RA), Left Atrium (LA) presents distinctive challenges, including much thinner myocardial walls, complex and irregular morphology, as well as diversity in individual's structure, making off-the-shelf methods designed for the Left
Externí odkaz:
http://arxiv.org/abs/2405.17518
Autor:
Lemus, Javier A., Herrmann, Benjamin
The sparse identification of nonlinear dynamics (SINDy) has been established as an effective technique to produce interpretable models of dynamical systems from time-resolved state data via sparse regression. However, to model parameterized systems,
Externí odkaz:
http://arxiv.org/abs/2405.08771
Autor:
López-Lemus, Jorge Armando, De la Garza Carranza, María Teresa, Revilla, Margarita Schmitt, López-Lemus, José Guadalupe
Publikováno v:
Innovar: Revista de ciencias administrativas y sociales, 2024 Apr 01. 34(92), 1-21.
Externí odkaz:
https://www.jstor.org/stable/27301211
Autor:
Liao, Chih-Tang, Lemus, Andrew, Gürbüz, Ali, Tsang, Alan C. H., Pak, On Shun, Daddi-Moussa-Ider, Abdallah
Microorganisms and synthetic microswimmers often encounter complex environments consisting of networks of obstacles embedded into viscous fluids. Such settings include biological media, such as mucus with filamentous networks, as well as environmenta
Externí odkaz:
http://arxiv.org/abs/2402.09793
Unsupervised learning has become a staple in classical machine learning, successfully identifying clustering patterns in data across a broad range of domain applications. Surprisingly, despite its accuracy and elegant simplicity, unsupervised learnin
Externí odkaz:
http://arxiv.org/abs/2312.16074