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Software bots, extensively adopted by Open Source Software (OSS) projects, support developers across several activities, from automating predefined tasks to generating code that aids software engineers. However, with the growing prominence of bots, q
Externí odkaz:
http://arxiv.org/abs/2411.09467
Autor:
Maevskiy, Artem, Carvalho, Alexandra, Sataev, Emil, Turchyna, Volha, Noori, Keian, Rodin, Aleksandr, Neto, A. H. Castro, Ustyuzhanin, Andrey
Discovering new superionic materials is essential for advancing solid-state batteries, which offer improved energy density and safety compared to the traditional lithium-ion batteries with liquid electrolytes. Conventional computational methods for i
Externí odkaz:
http://arxiv.org/abs/2411.06804
Autor:
Fonseca, Diogo, Neto, Pedro
In the quest for electrically-driven soft actuators, the focus has shifted away from liquid-gas phase transition, commonly associated with reduced strain rates and actuation delays, in favour of electrostatic and other electrothermal actuation method
Externí odkaz:
http://arxiv.org/abs/2411.06963
Autor:
Li, Tianbo, Lin, Min, Dale, Stephen, Shi, Zekun, Neto, A. H. Castro, Novoselov, Kostya S., Vignale, Giovanni
We present a novel approach to address the challenges of variable occupation numbers in direct optimization of density functional theory (DFT). By parameterizing both the eigenfunctions and the occupation matrix, our method minimizes the free energy
Externí odkaz:
http://arxiv.org/abs/2411.05033
Autor:
de Jesus, Gleydson Fernandes, Teixeira, Erico Souza, Galvão, Lucas Queiroz, da Silva, Maria Heloísa Fraga, Neto, Mauro Queiroz Nooblath, Fernandez, Bruno Oziel, Cruz, Clebson dos Santos
The Variational Quantum Eigensolver (VQE) is a promising hybrid algorithm, utilizing both quantum and classical computers to obtain the ground state energy of molecules. In this context, this study applies VQE to investigate the ground state of proto
Externí odkaz:
http://arxiv.org/abs/2411.00990
The Dzyaloshinskii-Lifshitz-Pitaevskii (DLP) theory of Casimir forces predicts a repulsion between two material surfaces separated by a third medium with an intermediate dielectric function. This DLP repulsion paradigm constitutes an important exampl
Externí odkaz:
http://arxiv.org/abs/2410.18961
Autor:
Marcondes, Diego, Braga-Neto, Ulisses
We propose generalized resubstitution error estimators for regression, a broad family of estimators, each corresponding to a choice of empirical probability measures and loss function. The usual sum of squares criterion is a special case correspondin
Externí odkaz:
http://arxiv.org/abs/2410.17948
We introduce DeepSets Operator Networks (DeepOSets), an efficient, non-autoregressive neural network architecture for in-context operator learning. In-context learning allows a trained machine learning model to learn from a user prompt without furthe
Externí odkaz:
http://arxiv.org/abs/2410.09298
Autor:
Marques, Leonardo B. de M. M., Ueda, Lucas H., Neto, Mário U., Simões, Flávio O., Runstein, Fernando, Bó, Bianca Dal, Costa, Paula D. P.
The goal of cross-speaker style transfer in TTS is to transfer a speech style from a source speaker with expressive data to a target speaker with only neutral data. In this context, we propose using a pre-trained singing voice conversion (SVC) model
Externí odkaz:
http://arxiv.org/abs/2410.05620
On October 3, 2024, the "Em\'ilias Podcast -- Women in Computing" celebrates its 5th anniversary, standing out as a platform that promotes the participation of women in STEM (an acronym for "science, technology, engineering, and mathematics"). The po
Externí odkaz:
http://arxiv.org/abs/2410.16294