Sparse grid interpolation is a popular numerical discretization technique for the treatment of high dimensional, multivariate problems. We consider the case of using time-series data to calibrate epidemiological models from both phenomenological and mechanistic perspectives using this computational tool. By ...
Smolyak Sparse Grid Library This library is an implementation of Smolyak’s Sparse Grid Algorithm for solving integration and interpolation problems in d-dim spaces with far fewer function evaluations than needed with traditional tensor production integration/interpolation. This library currently implements ...
Sparse grid combination technique in Python pythonsparse-grids UpdatedApr 3, 2019 Python A scientific Python project for sparse grid interpolation (a.k.a. stochastic collocation) with a focus on parametric coefficient PDEs. sparse-gridsadaptivitystochastic-collocation-femcombination-techniquesparse-grid-int...
algorithmallowsprojectionofhigh-dimensionaldatatoalow-dimensionalgrid. Throughthisprojectionandfocusingonitspropertyoftopologypreservation, SOMallowsnonlinearinterpolationformissingvalues. Thispaperdescribesanewmethod,whichcombinesseveralSOMsinorderto enhancetheaccuracyofthenonlinearinterpolation.Thecombinationisachieved witha...
The goal of pixel-wise interpolation is to map the time series pressure measure- ments of each sensor to the defined reconstruction grid on a pixel-basis, which results in a 3D data array with dimensions corresponding to the 2D image space and sensor number (Fig. 3b,c). This is ...
Variance-based global sensitivity analysis via sparse-grid interpolation and cubature. Commu- nications in Computational Physics 2011; 9(3):542-567.G.T. Buzzard and D. Xiu. Variance-based global sensitivity analysis via sparse-grid interpolation and cubature. Communications in Computational Physics,...
an algorithm for trigonometric interpolation involving only so-called standard information of multivariate functions on generalized sparse grids has been suggested and a study on its application for the interpolation of functions in periodic Sobolev spaces of dominating mixed smoothness has been presented. ...
In this work, we investigate from the empirical point of view an alternative procedure, which involves an interpolation of the complex field derived from the sparse phase measurements. Unlike traditional approaches, our method allows to bypass the PU step and obtain a regular-grid complex field ...
Bode. Workload Balancing on Heterogeneous Systems: A Case Study of Sparse Grid Interpolation. In Euro-Par 2011: Parallel Processing Workshops, pages 345-354. August 2012. LNCS 7156.A. Muraras赂u, J. Weidendorfer, and A. Bode, "Workload balancing on heterogeneous systems: A case study of ...
The clouds are generated using the sparse-grid interpolation method which is both error-controlled and computationally efficient. The approach is implemented on a differential drive vehicle.Sarah L. NobleJoel M. EspositoJason CaseProceedings of the ASME 6th annual dynamic systems and control conference...