Zobrazeno 1 - 10
of 66 142
pro vyhledávání: '"A, Mesquita"'
Autor:
Lopes, Rovan F., Tumelero, Milton A., de Araujo, Clodoaldo I. L., de Andrade, Antonio M. H., Mesquita, Fabiano, Carmo, Danusa, Colauto, F., Ortiz, W. A., Pureur, P.
The magnetic textures generated by a perpendicularly applied magnetic field at the ferromagnetic layer of $Co/Al_{2}O_{3}/Nb$ thin film heterostructures are investigated using magneto-optical imaging and micromagnetic simulations. It is observed that
Externí odkaz:
http://arxiv.org/abs/2410.18028
Generative Flow Networks (GFlowNets) are amortized inference models designed to sample from unnormalized distributions over composable objects, with applications in generative modeling for tasks in fields such as causal discovery, NLP, and drug disco
Externí odkaz:
http://arxiv.org/abs/2410.09355
Autor:
Mesquita-Piccione, Pietro
In this paper we develop an analogue of the Berkovich analytification for non-necessarily algebraic complex spaces. We apply this theory to generalize to arbitrary compact K\"ahler manifolds a result of Chi Li, proving that a stronger version of K-st
Externí odkaz:
http://arxiv.org/abs/2409.06221
GFlowNets are a promising alternative to MCMC sampling for discrete compositional random variables. Training GFlowNets requires repeated evaluations of the unnormalized target distribution or reward function. However, for large-scale posterior sampli
Externí odkaz:
http://arxiv.org/abs/2406.03288
Autor:
Junior, Carlos Alberto Durigan, Spinola, Mauro De Mesquita, Gonçalves, Rodrigo Franco, Laurindo, Fernando José Barbin
Central Bank Digital Currency (CBDC) can be defined as a virtual currency based on node network and digital encryption algorithm issued by a country which has a legal credit protection. CBDCs are supported by Distributed Ledger Technologies (DLTs), a
Externí odkaz:
http://arxiv.org/abs/2407.07898
Autor:
Benatto, Leandro, Mesquita, Omar, Roman, Kaike R. M. Pachecoand Lucimara S., Koehler, Marlus, Capaz, Rodrigo B., Candiotto, Graziâni
The Transfer Matrix Method (TMM) has become a prominent tool for the optical simulation of thin$-$film solar cells, particularly among researchers specializing in organic semiconductors and perovskite materials. As the commercial viability of these s
Externí odkaz:
http://arxiv.org/abs/2404.12191
Autor:
Garcia, Cristiano Mesquita, Koerich, Alessandro Lameiras, Britto Jr, Alceu de Souza, Barddal, Jean Paul
The proliferation of textual data on the Internet presents a unique opportunity for institutions and companies to monitor public opinion about their services and products. Given the rapid generation of such data, the text stream mining setting, which
Externí odkaz:
http://arxiv.org/abs/2403.15455
Autor:
Garcia, Cristiano Mesquita, Koerich, Alessandro Lameiras, Britto Jr, Alceu de Souza, Barddal, Jean Paul
Systems and individuals produce data continuously. On the Internet, people share their knowledge, sentiments, and opinions, provide reviews about services and products, and so on. Automatically learning from these textual data can provide insights to
Externí odkaz:
http://arxiv.org/abs/2403.12328
Deep neural networks are notoriously miscalibrated, i.e., their outputs do not reflect the true probability of the event we aim to predict. While networks for tabular or image data are usually overconfident, recent works have shown that graph neural
Externí odkaz:
http://arxiv.org/abs/2403.04605
The search for double Higgs production in $b\bar{b}W^+W^-$, where both $W$ bosons decay to leptons, has been rehabilitated as a good option to look for that key process to the Standard Model scalar sector study in the LHC. The missing neutrinos, howe
Externí odkaz:
http://arxiv.org/abs/2402.10273