High Dimensional Uncertainty Quantification for an Electrothermal Field Problem using Stochastic Collocation on Sparse Grids and Tensor Train Decomposition. - Dimitrios Loukrezis; Ulrich Römer; Thorben Casper; Sebastian Schöps; Herbert De Gersem (CoRR, 2016)

Numerical Comparison of Leja and Clenshaw-Curtis Dimension-Adaptive Collocation for Stochastic Parametric Electromagnetic Field Problems. - Dimitrios Loukrezis; Ulrich Römer; Herbert De Gersem (CoRR, 2017)

Uncertainty quantification for an optical grating coupler with an adjoint-based Leja adaptive collocation method. - Niklas Georg; Dimitrios Loukrezis; Ulrich Römer; Sebastian Schöps (CoRR, 2018)

Approximation and Uncertainty Quantification of Stochastic Systems with Arbitrary Input Distributions using Weighted Leja Interpolation. - Dimitrios Loukrezis; Herbert De Gersem (CoRR, 2019)

Adaptive Sparse Polynomial Chaos Expansions via Leja Interpolation. - Dimitrios Loukrezis; Herbert De Gersem (CoRR, 2019)

Robust Adaptive Least Squares Polynomial Chaos Expansions in High-Frequency Applications. - Dimitrios Loukrezis; Armin Galetzka; Herbert De Gersem (CoRR, 2019)

Approximation and Uncertainty Quantification of Systems with Arbitrary Parameter Distributions Using Weighted Leja Interpolation. - Dimitrios Loukrezis; Herbert De Gersem (Algorithms, 2020)

Magnetic Field Simulation with Data-Driven Material Modeling. - Herbert De Gersem; Armin Galetzka; Ion Gabriel Ion; Dimitrios Loukrezis; Ulrich Römer (CoRR, 2020)

Data-Driven Solvers for Strongly Nonlinear Material Response. - Armin Galetzka; Dimitrios Loukrezis; Herbert De Gersem (CoRR, 2020)

Tensor-train approximation of the chemical master equation and its application for parameter inference. - Ion Gabriel Ion; Christian Wildner; Dimitrios Loukrezis; Heinz Koeppl; Herbert De Gersem (CoRR, 2021)

Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models. - Katiana Kontolati; Dimitrios Loukrezis; Ketson R. M. dos Santos; Dimitrios G. Giovanis; Michael D. Shields (CoRR, 2021)

Three-Dimensional Data-Driven Electromagnetic Field Simulation using Real World Measurement Data. - Armin Galetzka; Dimitrios Loukrezis; Herbert De Gersem (CoRR, 2021)

A Neural Solver for Variational Problems on CAD Geometries with Application to Electric Machine Simulation. - Moritz von Tresckow; Stefan Kurz; Herbert De Gersem; Dimitrios Loukrezis (CoRR, 2021)

Tensor train based isogeometric analysis for PDE approximation on parameter dependent geometries. - Ion Gabriel Ion; Dimitrios Loukrezis; Herbert De Gersem (CoRR, 2022)

Power Module Heat Sink Design Optimization with Data-Driven Polynomial Chaos Surrogate Models. - Dimitrios Loukrezis; Herbert De Gersem (CoRR, 2022)

An hp-adaptive multi-element stochastic collocation method for surrogate modeling with information re-use. - Armin Galetzka; Dimitrios Loukrezis; Niklas Georg; Herbert De Gersem; Ulrich Römer (CoRR, 2022)

Quadrupole Magnet Design based on Genetic Multi-Objective Optimization. - Eric Diehl; Moritz von Tresckow; Lou Scholtissek; Dimitrios Loukrezis; Nicolas Marsic; Wolfgang F. O. Müller; Herbert De Gersem (CoRR, 2022)

A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems. - Katiana Kontolati; Dimitrios Loukrezis; Dimitrios G. Giovanis; Lohit Vandanapu; Michael D. Shields (J. Comput. Phys., 2022)

Data-driven Modified Nodal Analysis Circuit Solver. - Armin Galetzka; Dimitrios Loukrezis; Herbert De Gersem (CoRR, 2023)

Error Approximation and Bias Correction in Dynamic Problems using a Recurrent Neural Network/Finite Element Hybrid Model. - Moritz von Tresckow; Herbert De Gersem; Dimitrios Loukrezis (CoRR, 2023)

Multivariate sensitivity adaptive polynomial chaos expansion for vector valued surrogate modeling. - Dimitrios Loukrezis; Eric Diehl; Herbert De Gersem (CoRR, 2023)

UQpy v4.1: Uncertainty quantification with Python. - Dimitrios Tsapetis; Michael D. Shields; Dimitris G. Giovanis; Audrey Olivier; Lukás Novák; Promit Chakroborty; Himanshu Sharma; Mohit Singh Chauhan; Katiana Kontolati; Lohit Vandanapu; Dimitrios Loukrezis; Michael Gardner (SoftwareX, 2023)

Fourier-enhanced reduced-order surrogate modeling for uncertainty quantification in electric machine design. - Aylar Partovizadeh; Sebastian Schöps; Dimitrios Loukrezis (CoRR, 2024)

Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification. - Dimitris G. Giovanis; Dimitrios Loukrezis; Ioannis G. Kevrekidis; Michael D. Shields (J. Comput. Phys., 2024)