Zobrazeno 1 - 10
of 58 966
pro vyhledávání: '"A. Barrios"'
For many machine learning methods, creating a model requires setting a parameter that controls the model's capacity before training, e.g.~number of neurons in DNNs, or inducing points in GPs. Increasing capacity improves performance until all the inf
Externí odkaz:
http://arxiv.org/abs/2408.07588
Autor:
Barrios, Alexander, Cullinan, John
Let $\ell$ be an odd prime, and suppose $E$ is an elliptic curve defined over the rational numbers $\mathbb{Q}$. If $E$ has an $\ell$-torsion point, then there has been significant work done on characterizing the $\ell$-divisibility of the global Tam
Externí odkaz:
http://arxiv.org/abs/2408.03419
Using a recent characterization of energy-preserving B-series, we derive the explicit conditions on the coefficients of a Runge-Kutta method that ensure energy preservation (for Hamiltonian systems) up to a given order in the step size, which we refe
Externí odkaz:
http://arxiv.org/abs/2407.15365
Autor:
Gates, J. M., Orford, R., Rudolph, D., Appleton, C., Barrios, B. M., Benitez, J. Y., Bordeau, M., Botha, W., Campbell, C. M., Chadderton, J., Chemey, A. T., Clark, R. M., Crawford, H. L., Despotopulos, J. D., Dorvaux, O., Esker, N. E., Fallon, P., Folden III, C. M., Gall, B. J. P., Garcia, F. H., Golubev, P., Gooding, J. A., Grebo, M., Gregorich, K. E., Guerrero, M., Henderson, R. A., Herzberg, R. -D., Hrabar, Y., King, T. T., Covo, M. Kireeff, Kirkland, A. S., Krücken, R., Leistenschneider, E., Lykiardopoulou, E. M., McCarthy, M., Mildon, J. A., Müller-Gatermann, C., Phair, L., Pore, J. L., Rice, 1 E., Rykaczewski, K. P., Sammis, B. N., Sarmiento, L. G., Seweryniak, D., Sharp, D. K., Sinjari, A., Steinegger, P., Stoyer, M. A., Szornel, J. M., Thomas, K., Todd, D. S., Vo, P., Watson, V., Wooddy, P. T.
The $^{244}$Pu($^{50}$Ti,$xn$)$^{294-x}$Lv reaction was investigated at Lawrence Berkeley National Laboratory's 88-Inch Cyclotron facility. The experiment was aimed at the production of a superheavy element with $Z\ge 114$ by irradiating an actinide
Externí odkaz:
http://arxiv.org/abs/2407.16079
Autor:
Feldman, Matias, Vernier, Charles, Nag, Rahul, Barrios, Juan, Royer, Sébastien, Cruguel, Hervé, Lacaze, Emmanuelle, Lhuillier, Emmanuel, Fournier, Danièle, Schulz, Florian, Hamon, Cyrille, Portalès, Hervé, Utterback, James K.
Realizing tunable functional materials with built-in nanoscale heat flow directionality represents a significant challenge with the potential to enable novel thermal management strategies. Here we use spatiotemporally-resolved thermoreflectance to vi
Externí odkaz:
http://arxiv.org/abs/2407.08325
Autor:
Loutfi, Mahdi Ait Lhaj, Podasca, Teodora Boblea, Zwanenburg, Alex, Upadhaya, Taman, Barrios, Jorge, Raleigh, David R., Chen, William C., Capaldi, Dante P. I., Zheng, Hong, Gevaert, Olivier, Wu, Jing, Silva, Alvin C., Zhang, Paul J., Bai, Harrison X., Seuntjens, Jan, Löck, Steffen, Richard, Patrick O., Morin, Olivier, Reinhold, Caroline, Lepage, Martin, Vallières, Martin
Background: The high dimensionality of radiomic feature sets, the variability in radiomic feature types and potentially high computational requirements all underscore the need for an effective method to identify the smallest set of predictive feature
Externí odkaz:
http://arxiv.org/abs/2407.04888
Autor:
Sánchez-Sánchez, Jesús Arturo, Navarro-Espino, Montserrat, Barrios-Vargas, José Eduardo, Stegmann, Thomas
We investigate the electronic structure and transport properties of twisted bilayer graphene (TBLG) at a twist angle of $\theta\approx 1.696\text{{\deg}}$. Using a combination of molecular dynamics and tight-binding calculations, we find two superlat
Externí odkaz:
http://arxiv.org/abs/2407.04668
Autor:
Espinosa, C. Barrios, Sánchez, J., Appel, S., Becker, S., Krauß, J., Díaz, P. Martínez, Unger, L., Houillon, Marie, Loewe, Axel
Background: Computer models for simulating cardiac electrophysiology are valuable tools for research and clinical applications. Traditional reaction-diffusion (RD) models used for these purposes are computationally expensive. While eikonal models off
Externí odkaz:
http://arxiv.org/abs/2406.18619
Autor:
Jafrasteh, Bahram, Lubian-Lopez, Simon Pedro, Trimarco, Emiliano, Ruiz, Macarena Roman, Barrios, Carmen Rodriguez, Almagro, Yolanda Marin, Benavente-Fernandez, Isabel
In this study, we introduce MGA-Net, a novel mask-guided attention neural network, which extends the U-net model for precision neonatal brain imaging. MGA-Net is designed to extract the brain from other structures and reconstruct high-quality brain i
Externí odkaz:
http://arxiv.org/abs/2406.17709
Autor:
Barrios, Wayner, Jin, SouYoung
While the Self-Attention mechanism in the Transformer model has proven to be effective in many domains, we observe that it is less effective in more diverse settings (e.g. multimodality) due to the varying granularity of each token and the high compu
Externí odkaz:
http://arxiv.org/abs/2406.02761