Results 11 to 20 of about 88,361 (282)
A sparse-grid isogeometric solver [PDF]
Computer Methods in Applied Mechanics and Engineering, 2018 Isogeometric Analysis (IGA) typically adopts tensor-product splines and NURBS as a basis for the approximation of the solution of PDEs. In this work, we investigate to which extent IGA solvers can benefit from the so-called sparse-grids construction in its combination technique form, which was first introduced in the early 90s in the context of the ...
J Beck, G Sangalli, L Tamellini
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Sparse Grids and Applications - Stuttgart 2014 [PDF]
, 2016 Peng Chen and Christoph Schwab: Adaptive Sparse Grid Model Order Reduction for Fast Bayesian Estimation and Inversion.- Fabian Franzelin and Dirk Pfluger: From Data to Uncertainty: An E_cient Integrated Data-Driven Sparse Grid Approach to Propagate Uncertainty.- Helmut Harbrecht and Michael Peters: Combination Technique Based Second Moment Analysis for
A. Genz +13 more
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Estimation with Numerical Integration on Sparse Grids [PDF]
, 2006 For the estimation of many econometric models, integrals without analytical solutions have to be evaluated. Examples include limited dependent variables and nonlinear panel data models.
Heiss, Florian, Winschel, Viktor
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sparse-ir: Optimal compression and sparse sampling of many-body propagators
SoftwareX, 2023 We introduce sparse-ir, a collection of libraries to efficiently handle imaginary-time propagators, a central object in finite-temperature quantum many-body calculations. We leverage two concepts: firstly, the intermediate representation (IR), an optimal
Markus Wallerberger +17 more
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Sensors, 2019 Exploring large, unknown, and unstructured environments is challenging for Unmanned Aerial Vehicles (UAVs), but they are valuable tools to inspect large structures safely and efficiently.
Margarida Faria +4 more
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Entropy, 2013 Molecular modeling is an important subdomain in the field of computational modeling, regarding both scientific and industrial applications. This is because computer simulations on a molecular level are a virtuous instrument to study the impact of ...
Dirk Reith, Marco Hülsmann
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Sparse grid distance transforms
Graphical Models, 2010 We present a Sparse Grid Distance Transform (SGDT), an algorithm for computing and storing large distance fields. Although SGDT is based on a divide-and-conquer algorithm for distance transforms, its data structure is quite simplified. Our observations revealed that distance fields can be recovered from distance fields of sub-block cluster boundaries ...
Takashi Michikawa, Hiromasa Suzuki
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Heterogeneous Distributed Big Data Clustering on Sparse Grids
Algorithms, 2019 Clustering is an important task in data mining that has become more challenging due to the ever-increasing size of available datasets. To cope with these big data scenarios, a high-performance clustering approach is required.
David Pfander +2 more
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Suboptimal feedback control of PDEs by solving HJB equations on adaptive sparse grids [PDF]
, 2015 International audienceAn approach to solve finite time horizon suboptimal feedback control problems for partial differential equations is proposed by solving dynamic programming equations on adaptive sparse grids. The approach is illustrated for the wave
Garcke, Jochen, Kröner, Axel
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A Multiple Target Localization with Sparse Information in Wireless Sensor Networks
International Journal of Distributed Sensor Networks, 2016 It is a great challenge for wireless sensor network to provide enough information for targets localization due to the limits on application environment and its nature, such as energy, communication, and sensing precision.
Liping Liu +3 more
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