Zobrazeno 1 - 10
of 9 935
pro vyhledávání: '"A. Danis"'
Autor:
Danis, M. Engin, Durbin, Paul
This study highlights the importance of satisfying the eddy viscosity equivalence below the logarithmic layer, to deriving accurate compressibility transformations. First, we analyze the ability of known transformations to satisfy the eddy viscosity
Externí odkaz:
http://arxiv.org/abs/2410.01915
Autor:
Danis, Mustafa Engin, Truong, Duc P., DeSantis, Derek, Petersen, Mark, Rasmussen, Kim O., Alexandrov, Boian S.
In this paper, we introduce a high-order tensor-train (TT) finite volume method for the Shallow Water Equations (SWEs). We present the implementation of the $3^{rd}$ order Upwind and the $5^{th}$ order Upwind and WENO reconstruction schemes in the TT
Externí odkaz:
http://arxiv.org/abs/2408.03483
Publikováno v:
Phys. Rev. B 110, L060409 (2024)
The presence of spin-polarized charge carriers in metallic magnets provides a mechanism for spin-lattice interactions mediated by electron-phonon coupling. Here, we present a theory of this mechanism used to estimate its effect on the exchange intera
Externí odkaz:
http://arxiv.org/abs/2406.05229
Spectral methods provide highly accurate numerical solutions for partial differential equations, exhibiting exponential convergence with the number of spectral nodes. Traditionally, in addressing time-dependent nonlinear problems, attention has been
Externí odkaz:
http://arxiv.org/abs/2406.02505
Autor:
Danis, Mustafa Engin, Truong, Duc, Boureima, Ismael, Korobkin, Oleg, Rasmussen, Kim, Alexandrov, Boian
In this study, we introduce a tensor-train (TT) finite difference WENO method for solving compressible Euler equations. In a step-by-step manner, the tensorization of the governing equations is demonstrated. We also introduce \emph{LF-cross} and \emp
Externí odkaz:
http://arxiv.org/abs/2405.12301
One of the ways to make artificial intelligence more natural is to give it some room for doubt. Two main questions should be resolved in that way. First, how to train a model to estimate uncertainties of its own predictions? And then, what to do with
Externí odkaz:
http://arxiv.org/abs/2404.10314
Today, machine learning tools, particularly artificial neural networks, have become crucial for diverse applications. However, current digital computing tools to train and deploy artificial neural networks often struggle with massive data sizes and h
Externí odkaz:
http://arxiv.org/abs/2403.12490
Autor:
Alukaev, Danis, Kiselev, Semen, Pershin, Ilya, Ibragimov, Bulat, Ivanov, Vladimir, Kornaev, Alexey, Titov, Ivan
Concept Bottleneck Models (CBMs) assume that training examples (e.g., x-ray images) are annotated with high-level concepts (e.g., types of abnormalities), and perform classification by first predicting the concepts, followed by predicting the label r
Externí odkaz:
http://arxiv.org/abs/2310.14805
Autor:
Zélia Bontemps, Danis Abrouk, Sita Venier, Pierre Vergne, Serge Michalet, Gilles Comte, Yvan Moënne-Loccoz, Mylène Hugoni
Publikováno v:
npj Biofilms and Microbiomes, Vol 10, Iss 1, Pp 1-13 (2024)
Abstract Tourism in Paleolithic caves can cause an imbalance in cave microbiota and lead to cave wall alterations, such as dark zones. However, the mechanisms driving dark zone formation remain unclear. Using shotgun metagenomics in Lascaux Cave’s
Externí odkaz:
https://doaj.org/article/4ce4b888e0d44362b632b4278c19d483
Autor:
Guy Karlebach, Robin Steinhaus, Daniel Danis, Maeva Devoucoux, Olga Anczuków, Gloria Sheynkman, Dominik Seelow, Peter N. Robinson
Publikováno v:
npj Genomic Medicine, Vol 9, Iss 1, Pp 1-10 (2024)
Abstract Numerous factors regulate alternative splicing of human genes at a co-transcriptional level. However, how alternative splicing depends on the regulation of gene expression is poorly understood. We leveraged data from the Genotype-Tissue Expr
Externí odkaz:
https://doaj.org/article/39c63d49bd6b460c87475b63ca1475dd