
Identification of unknown parameters and prediction with hierarchical matrices
Statistical analysis of massive datasets very often implies expensive li...
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Solving weakly supervised regression problem using lowrank manifold regularization
We solve a weakly supervised regression problem. Under "weakly" we under...
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PostProcessing of HighDimensional Data
Scientific computations or measurements may result in huge volumes of da...
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Solution of the 3D densitydriven groundwater flow problem with uncertain porosity and permeability
As groundwater is an essential nutrition and irrigation resource, its po...
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Propagation of Uncertainties in DensityDriven Flow
Accurate modeling of contamination in subsurface flow and water aquifers...
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Kriging in Tensor Train data format
Combination of lowtensor rank techniques and the Fast Fourier transform...
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SemiSupervised Regression using Cluster Ensemble and LowRank CoAssociation Matrix Decomposition under Uncertainties
In this paper, we solve a semisupervised regression problem. Due to the...
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HLIBCov: Parallel Hierarchical Matrix Approximation of Large Covariance Matrices and Likelihoods with Applications in Parameter Identification
The main goal of this article is to introduce the parallel hierarchical ...
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Likelihood Approximation With Hierarchical Matrices For Large Spatial Datasets
We use available measurements to estimate the unknown parameters (varian...
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Alexander Litvinenko
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