
A Neural Solver for Variational Problems on CAD Geometries with Application to Electric Machine Simulation
This work presents a deep learningbased framework for the solution of p...
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Grassmannian diffusion maps based surrogate modeling via geometric harmonics
In this paper, a novel surrogate model based on the Grassmannian diffusi...
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ThreeDimensional DataDriven Magnetostatic Field Computation using RealWorld Measurement Data
This paper presents a practical case study of a datadriven magnetostati...
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Manifold learningbased polynomial chaos expansions for highdimensional surrogate models
In this work we introduce a manifold learningbased method for uncertain...
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Tensortrain approximation of the chemical master equation and its application for parameter inference
In this work, we perform Bayesian inference tasks for the chemical maste...
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Local field reconstruction from rotating coil measurements in particle accelerator magnets
In this paper a general approach to reconstruct three dimensional field ...
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DataDriven Solvers for Strongly Nonlinear Material Response
This work presents a datadriven magnetostatic finiteelement solver tha...
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Magnetic Field Simulation with DataDriven Material Modeling
This paper developes a datadriven magnetostatic finiteelement (FE) sol...
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Robust Adaptive Least Squares Polynomial Chaos Expansions in HighFrequency Applications
We present an algorithm for computing sparse, least squaresbased polyno...
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Adaptive Sparse Polynomial Chaos Expansions via Leja Interpolation
This work suggests an interpolationbased stochastic collocation method ...
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Approximation and Uncertainty Quantification of Stochastic Systems with Arbitrary Input Distributions using Weighted Leja Interpolation
Approximation and uncertainty quantification methods based on Lagrange i...
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Uncertainty quantification for an optical grating coupler with an adjointbased Leja adaptive collocation method
This paper addresses uncertainties arising in the nanoscale fabrication...
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Assessing the Performance of Leja and ClenshawCurtis Collocation for Computational Electromagnetics with Random Input Data
We consider the problem of quantifying uncertainty regarding the output ...
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Numerical Comparison of Leja and ClenshawCurtis DimensionAdaptive Collocation for Stochastic Parametric Electromagnetic Field Problems
We consider the problem of approximating the output of a parametric elec...
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Dimitrios Loukrezis
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