Institution
Technical University of Dortmund
Education•Dortmund, Nordrhein-Westfalen, Germany•
About: Technical University of Dortmund is a education organization based out in Dortmund, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Context (language use) & Large Hadron Collider. The organization has 13028 authors who have published 27666 publications receiving 615557 citations. The organization is also known as: Dortmund University & University of Dortmund.
Topics: Context (language use), Large Hadron Collider, Computer science, Neutrino, Finite element method
Papers published on a yearly basis
Papers
More filters
••
TL;DR: This study shows that the extruded magnesium alloy LAE442 provides low corrosion rates and reacts in vivo with an acceptable host response and the in vivo corrosion rate can be further reduced by additional MgF(2) coating.
389 citations
••
TL;DR: It appears well established that the aromatic amine components from azo pigments based on 3,3'-dichlorobenzidine are practically not bioavailable, and it is very unlikely that occupational exposure to insoluble azo Pigments would be associated with a substantial risk of (bladder) cancer in man.
388 citations
••
01 Jan 2018TL;DR: This work presents Spline-based Convolutional Neural Networks (SplineCNNs), a variant of deep neural networks for irregular structured and geometric input, e.g., graphs or meshes, that is a generalization of the traditional CNN convolution operator by using continuous kernel functions parametrized by a fixed number of trainable weights.
Abstract: We present Spline-based Convolutional Neural Networks (SplineCNNs), a variant of deep neural networks for irregular structured and geometric input, e.g., graphs or meshes. Our main contribution is a novel convolution operator based on B-splines, that makes the computation time independent from the kernel size due to the local support property of the B-spline basis functions. As a result, we obtain a generalization of the traditional CNN convolution operator by using continuous kernel functions parametrized by a fixed number of trainable weights. In contrast to related approaches that filter in the spectral domain, the proposed method aggregates features purely in the spatial domain. In addition, SplineCNN allows entire end-to-end training of deep architectures, using only the geometric structure as input, instead of handcrafted feature descriptors. For validation, we apply our method on tasks from the fields of image graph classification, shape correspondence and graph node classification, and show that it outperforms or pars state-of-the-art approaches while being significantly faster and having favorable properties like domain-independence. Our source code is available on GitHub1.
388 citations
••
TL;DR: In this article, the authors measured the isospin asymmetries of the B (0) -> K ( 0) mu (+) mu (-), B (1) → K (1)-m (+) m mu (-) and B (2)→ K (2)-m (-) m (-), respectively.
Abstract: The isospin asymmetries of B -> K mu (+) mu (-) and B -> K (*) mu (+) mu (-) decays and the partial branching fractions of the B (0) -> K (0) mu (+) mu (-), B (+) -> K (+) mu (+) mu (-) and B (+) -> K (*+) mu (+) mu (-) decays are measured as functions of the dimuon mass squared, q (2). The data used correspond to an integrated luminosity of 3 fb(-1) from proton-proton collisions collected with the LHCb detector at centre-of-mass energies of 7 TeV and 8 TeV in 2011 and 2012, respectively. The isospin asymmetries are both consistent with the Standard Model expectations. The three measured branching fractions favour lower values than their respective theoretical predictions, however they are all individually consistent with the Standard Model.
386 citations
••
TL;DR: In this paper, a systematic analysis of B meson decays into pions has been performed for decay modes with 2−7 pions in the final state, and the upper limits obtained on various branching ratios are consistent with the current model predictions.
386 citations
Authors
Showing all 13240 results
Name | H-index | Papers | Citations |
---|---|---|---|
Hermann Kolanoski | 145 | 1279 | 96152 |
Marc Besancon | 143 | 1799 | 106869 |
Kerstin Borras | 133 | 1341 | 92173 |
Emmerich Kneringer | 129 | 1021 | 80898 |
Achim Geiser | 129 | 1331 | 84136 |
Valerio Vercesi | 129 | 937 | 79519 |
Jens Weingarten | 128 | 896 | 74667 |
Giuseppe Mornacchi | 127 | 894 | 75830 |
Kevin Kroeninger | 126 | 836 | 70010 |
Daniel Muenstermann | 126 | 885 | 70855 |
Reiner Klingenberg | 126 | 733 | 70069 |
Claus Gössling | 126 | 775 | 71975 |
Diane Cinca | 126 | 822 | 70126 |
Frank Meier | 124 | 677 | 64889 |
Daniel Dobos | 124 | 679 | 67434 |