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检索条件"机构=Fraunhofer Center for Machine Learning and Institute for Algorithms and Scientific Computing SCAI"
37 条 记 录,以下是11-20 订阅
排序:
Wavelet-Packets for Deepfake Image Analysis and Detection
arXiv
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arXiv 2021年
作者: Wolter, Moritz Blanke, Felix Heese, Raoul Garcke, Jochen High Performance Computing & Analytics Lab Universität Bonn Germany Fraunhofer SCAI University of Bonn Germany Fraunhofer Center for Machine Learning Fraunhofer ITWM Germany Institute for Numerical Simulation University of Bonn Germany Fraunhofer Center for Machine Learning Fraunhofer SCAI Germany
As neural networks become able to generate realistic artificial images, they have the potential to improve movies, music, video games and make the internet an even more creative and inspiring place. Yet, the latest te... 详细信息
来源: 评论
Deep neural networks and PIDE discretizations
arXiv
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arXiv 2021年
作者: Bohn, Bastian Griebel, Michael Kannan, Dinesh Fraunhofer Center for Machine Learning Schloss Birlinghoven Sankt Augustin53754 Germany Fraunhofer Institute for Algorithms and Scientific Computing SCAI Schloss Birlinghoven Sankt Augustin53754 Germany Institute for Numerical Simulation University of Bonn Friedrich-Hirzebruch-Allee 7 Bonn53115 Germany
In this paper, we propose neural networks that tackle the problems of stability and field-of-view of a Convolutional Neural Network (CNN). As an alternative to increasing the network's depth or width to improve pe... 详细信息
来源: 评论
Similarity of particle systems using an invariant root mean square deviation measure
arXiv
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arXiv 2021年
作者: Bulin, Johannes Hamaekers, Jan Department of Virtual Material Design Fraunhofer Institute for Algorithms and Scientific Computing Schloss Birlinghoven Sankt Augustin53757 Germany Fraunhofer Center for Machine Learning Schloss Birlinghoven Sankt Augustin53757 Germany
Determining whether two particle systems are similar is a common problem in particle simulations. When the comparison should be invariant under permutations, orthogonal transformations, and translations of the systems... 详细信息
来源: 评论
Predicting dementia in people with Parkinson’s disease
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npj Parkinson's Disease 2025年 第1期11卷 1-10页
作者: Aborageh, Mohamed Hähnel, Tom Martins Conde, Patricia Klucken, Jochen Fröhlich, Holger Department of Bioinformatics Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Augustin Sankt 53757 Germany Department of Neurology University Hospital and Faculty of Medicine Carl Gustav Carus TUD Dresden University of Technology Dresden Germany Luxembourg Centre for Systems Biomedicine (LCSB) University of Luxembourg Esch-sur-Alzette Luxembourg Centre Hospitalier de Luxembourg (CHL) Luxembourg Luxembourg Bonn-Aachen International Center for Information Technology (B-IT) Rheinische Friedrich-Wilhelms-Universität Bonn Bonn 53115 Germany
Parkinson’s disease (PD) exhibits a variety of symptoms, with approximately 25% of patients experiencing mild cognitive impairment and 45% developing dementia within ten years of diagnosis. Predicting this progressio...
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Predictive analytics in quality assurance for assembly processes: lessons learned from a case study at an industry 4.0 demonstration cell
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Procedia CIRP 2021年 104卷 641-646页
作者: Peter Burggräf Johannes Wagner Benjamin Heinbach Fabian Steinberg Alejandro R. Pérez M. Lennart Schmallenbach Jochen Garcke Daniela Steffes-lai Moritz Wolter Chair of International Production Engineering and Management (IPEM) Universität Siegen Paul-Bonatz-Straße 9-11 57076 Siegen Germany Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Schloss Birlinghoven 1 53757 Sankt Augustin Germany Fraunhofer Center for Machine Learning Schloss Birlinghoven 1 53757 Sankt Augustin Germany Institute for Numerical Simulation Universität Bonn Endenicher Allee 19b 53115 Bonn Germany Institute for Computer Science Universität Bonn Endenicher Allee 19a 53115 Bonn Germany
Quality assurance (QA) is an important task in manufacturing to assess whether products meet their specifications. However, QA might be expensive, time-consuming, or incomplete. This paper presents a solution for pred... 详细信息
来源: 评论
SYNTHETIC DATA GENERATION FOR A LONGITUDINAL COHORT STUDY - EVALUATION, METHOD EXTENSION AND REPRODUCTION OF PUBLISHED DATA ANALYSIS RESULTS
arXiv
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arXiv 2023年
作者: Kühnel, Lisa Schneider, Julian Perrar, Ines Adams, Tim Prasser, Fabian Nöthlings, Ute Fröhlich, Holger Fluck, Juliane Knowledge Management Zb Med Information Centre for Life Sciences Cologne50931 Germany Faculty of Technology Bielefeld University Bielefeld33615 Germany Institute of Nutritional and Food Sciences - Nutritional Epidemiology University of Bonn Bonn53115 Germany Department of Bioinformatics Fraunhofer Institute for Algorithms and Scientific Computing Scai Sankt Augustin53757 Germany Medical Informatics Group Berlin Institute of Health Charité - Universitätsmedizin Berlin Berlin10117 Germany Bonn-Aachen International Center for It University of Bonn Friedrich Hirzebruch-Allee 6 Bonn53115 Germany The Agricultural Faculty University of Bonn Bonn53115 Germany
Access to individual-level health data is essential for gaining new insights and advancing science. In particular, modern methods based on artificial intelligence rely on the availability of and access to large datase... 详细信息
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Scalable hyperparameter optimization with lazy Gaussian processes
arXiv
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arXiv 2020年
作者: Ram, Raju Müller, Sabine Pfreundt, Franz-Josef Gauger, Nicolas R. Keuper, Janis Competence Center High Performance Computing Fraunhofer ITWM Kaiserslautern Germany Fraunhofer Center Machine Learning Germany Scientific Computing Group TU Kaiserslautern Germany Institute for Machine Learning and Analytics Offenburg University Germany
Most machine learning methods require careful selection of hyper-parameters in order to train a high performing model with good generalization abilities. Hence, several automatic selection algorithms have been introdu... 详细信息
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Combating mode collapse in GAN training: An empirical analysis using hessian eigenvalues
arXiv
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arXiv 2020年
作者: Lopez, Ricard Durall Chatzimichailidis, Avraam Labus, Peter Keuper, Janis Fraunhofer ITWM Germany IWR University of Heidelberg Germany Chair for Scientific Computing TU Kaiserslautern Germany Fraunhofer Center Machine Learning Germany Institute for Machine Learning and Analytics Offenburg University Germany
Generative adversarial networks (GANs) provide state-of-the-art results in image generation. However, despite being so powerful, they still remain very challenging to train. This is in particular caused by their highl... 详细信息
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Assessing the landscape of Alzheimer’s disease cohort data
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Alzheimer's & Dementia 2020年 第S4期16卷
作者: Colin Birkenbihl Yasamin Salimi Daniel Domingo-Fernández Holger Fröhlich Martin Hofmann-Apitius Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Sankt Augustin Germany Bonn-Aachen International Center for IT (b-it) Bonn Germany Fraunhofer Institute for Algorithms and Scientific Computing SCAI Sankt Augustin Germany
Background Data collected in cohort studies lay the groundwork for a plethora of Alzheimer’s disease (AD) research endeavours. While there exist numerous cohort datasets in our field, few dedicated efforts have focus...
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The recovery of ridge functions on the hypercube suffers from the curse of dimensionality
arXiv
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arXiv 2019年
作者: Doerr, Benjamin Mayer, Sebastian Ecole Polytechnique CS35003 Palaiseau91120 France Fraunhofer Center for Machine Learning Fraunhofer-Institute for Algo-rithms and Scientific Computing SCAI Schloss Birlinghoven Sankt Augustin53754 Germany
A multivariate ridge function is a function of the form f(x) = g(aT x), where g is univariate and a ∈ Rd. We show that the recovery of an unknown ridge function defined on the hypercube [-1, 1]d with Lipschitz-regula... 详细信息
来源: 评论