Zobrazeno 1 - 10
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pro vyhledávání: '"Ordóñez, A."'
Autor:
Alexeev, G. D., Alexeev, M. G., Alice, C., Amoroso, A., Andrieux, V., Anosov, V., Augsten, K., Augustyniak, W., Azevedo, C. D. R., Badelek, B., Barth, J., Beck, R., Beckers, J., Bedfer, Y., Bernhard, J., Bodlak, M., Bradamante, F., Bressan, A., Chang, W. -C., Chatterjee, C., Chiosso, M., Chung, S. -U., Cicuttin, A., Correia, P. M. M., Crespo, M. L., D'Ago, D., Torre, S. Dalla, Dasgupta, S. S., Dasgupta, S., Delcarro, F., Denisenko, I., Denisov, O. Yu., Donskov, S. V., Doshita, N., Dreisbach, Ch., Dünnweber, W., Dusaev, R. R., Ecker, D., Eremeev, D., Faccioli, P., Faessler, M., Finger, M., Finger jr., M., Fischer, H., Flöthner, K. J., Florian, W., Friedrich, J. M., Frolov, V., Ordòñez, L. G. Garcia, Gavrichtchouk, O. P., Gerassimov, S., Giarra, J., Giordano, D., Grasso, A., Gridin, A., Perdekamp, M. Grosse, Grube, B., Grüner, M., Guskov, A., Haas, P., von Harrach, D., Hoffmann, M., d'Hose, N., Hsieh, C. -Y., Ishimoto, S., Ivanov, A., Iwata, T., Jary, V., Joosten, R., Kabuß, E., Kaspar, F., Kerbizi, A., Ketzer, B., Khatun, A., Khaustov, G. V., Klein, F., Koivuniemi, J. H., Kolosov, V. N., Horikawa, K. Kondo, Konorov, I., Korzenev, A. Yu., Kotzinian, A. M., Kouznetsov, O. M., Koval, A., Kral, Z., Kunne, F., Kurek, K., Kurjata, R. P., Lavickova, K., Levorato, S., Lian, Y. -S., Lichtenstadt, J., Lin, P. -J., Longo, R., Lyubovitskij, V. E., Maggiora, A., Makke, N., Mallot, G. K., Maltsev, A., Martin, A., Marzec, J., Matoušek, J., Matsuda, T., Pires, C. Menezes, Metzger, F., Meyer, W., Mikhailov, Yu. V., Mikhasenko, M., Mitrofanov, E., Miura, D., Miyachi, Y., Molina, R., Moretti, A., Nagaytsev, A., Neyret, D., Niemiec, M., Nový, J., Nowak, W. -D., Nukazuka, G., Olshevsky, A. G., Ostrick, M., Panzieri, D., Parsamyan, B., Paul, S., Pekeler, H., Peng, J. -C., Pešek, M., Peshekhonov, D. V., Pešková, M., Platchkov, S., Pochodzalla, J., Polyakov, V. A., Quintans, C., Reicherz, G., Riedl, C., Ryabchikov, D. I., Rychter, A., Rymbekova, A., Samoylenko, V. D., Sandacz, A., Sarkar, S., Savin, I. A., Sbrizzai, G., Schmieden, H., Selyunin, A., Sinha, L., Spülbeck, D., Srnka, A., Stolarski, M., Sulc, M., Suzuki, H., Tessaro, S., Tessarotto, F., Thiel, A., Tosello, F., Townsend, A., Triloki, T., Tskhay, V., Valinoti, B., Veit, B. M., Veloso, J. F. C. A., Vijayakumar, A., Virius, M., Wagner, M., Wallner, S., Zaremba, K., Zavertyaev, M., Zemko, M., Zemlyanichkina, E., Ziembicki, M.
The multiplicities of positive and negative pions, kaons and unidentified hadrons produced in deep-inelastic scattering are measured in bins of the Bjorken scaling variable $x$, the relative virtual-photon energy $y$ and the fraction of the virtual-p
Externí odkaz:
http://arxiv.org/abs/2410.12005
Speculative decoding has proven to be an efficient solution to large language model (LLM) inference, where the small drafter predicts future tokens at a low cost, and the target model is leveraged to verify them in parallel. However, most existing wo
Externí odkaz:
http://arxiv.org/abs/2410.05589
Autor:
Rempfer, Benjamin, Ordonez, Gonzalo
We analytically model a one-dimensional lattice with periodic impurities representing a photonic crystal from first principles. We then investigate bound states in the continuum by computing the transmission and reflection coefficients. It turns out
Externí odkaz:
http://arxiv.org/abs/2410.05476
The Heckman selection model is one of the most well-renounced econometric models in the analysis of data with sample selection. This model is designed to rectify sample selection biases based on the assumption of bivariate normal error terms. However
Externí odkaz:
http://arxiv.org/abs/2409.12348
Nordic skiing provides fascinating opportunities for mathematical modelling studies that exploit methods and insights from physics, applied mathematics, data analysis, scientific computing and sports science. A typical ski course winds over varied te
Externí odkaz:
http://arxiv.org/abs/2410.02767
Recent work has shown that training wide neural networks with gradient descent is formally equivalent to computing the mean of the posterior distribution in a Gaussian Process (GP) with the Neural Tangent Kernel (NTK) as the prior covariance and zero
Externí odkaz:
http://arxiv.org/abs/2409.03953
In non-relativistic physics the concepts of geometry and topology are usually applied to characterise spatial structures, or structures in momentum space. We introduce the concept of temporal geometry, which encompasses the geometric and topological
Externí odkaz:
http://arxiv.org/abs/2409.02500
Autor:
Bergna, Richard, Calvo-Ordoñez, Sergio, Opolka, Felix L., Liò, Pietro, Hernandez-Lobato, Jose Miguel
We address the problem of learning uncertainty-aware representations for graph-structured data. While Graph Neural Ordinary Differential Equations (GNODE) are effective in learning node representations, they fail to quantify uncertainty. To address t
Externí odkaz:
http://arxiv.org/abs/2408.16115
Autor:
Alinea, Allan L., Ordonez, Joshwa DJ.
Motivated by an inclination for symmetry and possible extension of the General Theory of Relativity within the framework of Scalar Theory, we investigate the Bekenstein's disformal transformation of the Einstein-Hilbert action. Owing to the complicat
Externí odkaz:
http://arxiv.org/abs/2408.06915
Autor:
Alinea, Allan L., Ordonez, Joshwa DJ.
Although with great successes in explaining phenomena and natural behaviour involving the Universe or a part thereof, the General Theory of Relativity is far from a complete theory. Focusing on its extension within the framework of scalar tensor theo
Externí odkaz:
http://arxiv.org/abs/2408.06176