Zobrazeno 1 - 10
of 167 789
pro vyhledávání: '"Tavares, A"'
Autor:
Tavares, Ramon
This study presents a comprehensive methodology for modeling and forecasting the historical time series of fire spots detected by the AQUA_M-T satellite in the Amazon, Brazil. The approach utilizes a mixed Recurrent Neural Network (RNN) model, combin
Externí odkaz:
http://arxiv.org/abs/2409.02681
Recent advances in audio-text cross-modal contrastive learning have shown its potential towards zero-shot learning. One possibility for this is by projecting item embeddings from pre-trained backbone neural networks into a cross-modal space in which
Externí odkaz:
http://arxiv.org/abs/2408.13068
Topological defect lines (TDLs) in two-dimensional conformal field theories (CFTs) are standard examples of generalized symmetries in quantum field theory. Integrable lattice incarnations of these TDLs, such as those provided by spin/anyonic chains,
Externí odkaz:
http://arxiv.org/abs/2408.08241
We introduce a mechanism by which a misaligned ALP can be dynamically converted into a dark photon in the presence of a background magnetic field. An abundance of non-relativistic ALPs will convert to dark photons with momentum of order the inhomogen
Externí odkaz:
http://arxiv.org/abs/2408.03370
Let $f: M\rightarrow M$ be a continuous map on a compact metric space $M$ equipped with a fixed metric $d$, and let $\tau$ be the topology on $M$ induced by $d$. First, we will establish some fundamental properties of the mean Hausdorff dimension. Fu
Externí odkaz:
http://arxiv.org/abs/2407.08548
Autor:
Margraf, Valentin, Wever, Marcel, Gilhuber, Sandra, Tavares, Gabriel Marques, Seidl, Thomas, Hüllermeier, Eyke
In settings where only a budgeted amount of labeled data can be afforded, active learning seeks to devise query strategies for selecting the most informative data points to be labeled, aiming to enhance learning algorithms' efficiency and performance
Externí odkaz:
http://arxiv.org/abs/2406.17322
Autor:
Silva, Bernardo, Fontinele, Jefferson, Vieira, Carolina Letícia Zilli, Tavares, João Manuel R. S., Cury, Patricia Ramos, Oliveira, Luciano
Dental panoramic radiographs offer vast diagnostic opportunities, but training supervised deep learning networks for automatic analysis of those radiology images is hampered by a shortage of labeled data. Here, a different perspective on this problem
Externí odkaz:
http://arxiv.org/abs/2406.17915
Publikováno v:
Rend. Circ. Mat. Palermo Ser. 2 (2024), 14 pp
We consider a multiphase spectral problem on a stratified Lie group. We prove the existence of an eigenfunction of $(2,q)$-eigenvalue problem on a bounded domain. Furthermore, we also establish a Pohozaev-like identity corresponding to the problem on
Externí odkaz:
http://arxiv.org/abs/2405.14308
Autor:
Rodari, Giovanni, Novo, Leonardo, Albiero, Riccardo, Suprano, Alessia, Tavares, Carlos T., Caruccio, Eugenio, Hoch, Francesco, Giordani, Taira, Carvacho, Gonzalo, Gardina, Marco, Di Giano, Niki, Di Giorgio, Serena, Corrielli, Giacomo, Ceccarelli, Francesco, Osellame, Roberto, Spagnolo, Nicolò, Galvão, Ernesto F., Sciarrino, Fabio
Multiphoton indistinguishability is a central resource for quantum enhancement in sensing and computation. Developing and certifying large scale photonic devices requires reliable and accurate characterization of this resource, preferably using metho
Externí odkaz:
http://arxiv.org/abs/2404.18636
This paper studies Schauder theory to transmission problems modelled by fully nonlinear uniformly elliptic equations of second order. We focus on operators F that fails to be concave or convex in the space of symmetric matrices. In a first scenario,
Externí odkaz:
http://arxiv.org/abs/2404.16602