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ORCIDDimitrios Loukrezis
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2020 – today
- 2024
[j4]Dimitris G. Giovanis
, Dimitrios Loukrezis, Ioannis G. Kevrekidis, Michael D. Shields:
Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification. J. Comput. Phys. 519: 113443 (2024)- [i22]Dimitris G. Giovanis, Dimitrios Loukrezis, Ioannis G. Kevrekidis, Michael D. Shields:
Polynomial Chaos Expansions on Principal Geodesic Grassmannian Submanifolds for Surrogate Modeling and Uncertainty Quantification. CoRR abs/2401.16683 (2024) - 2023
- [j3]Dimitrios Tsapetis, Michael D. Shields, Dimitris G. Giovanis, Audrey Olivier, Lukás Novák, Promit Chakroborty, Himanshu Sharma, Mohit Chauhan, Katiana Kontolati, Lohit Vandanapu, Dimitrios Loukrezis, Michael Gardner:
UQpy v4.1: Uncertainty quantification with Python. SoftwareX 24: 101561 (2023) - [i21]Armin Galetzka, Dimitrios Loukrezis, Herbert De Gersem:
Data-driven Modified Nodal Analysis Circuit Solver. CoRR abs/2303.03401 (2023) - [i20]Dimitrios Tsapetis, Michael D. Shields, Dimitris G. Giovanis, Audrey Olivier, Lukás Novák, Promit Chakroborty, Himanshu Sharma, Mohit Chauhan, Katiana Kontolati, Lohit Vandanapu, Dimitrios Loukrezis, Michael Gardner:
UQpy v4.1: Uncertainty Quantification with Python. CoRR abs/2305.09572 (2023) - [i19]Moritz von Tresckow, Herbert De Gersem, Dimitrios Loukrezis:
Error Approximation and Bias Correction in Dynamic Problems using a Recurrent Neural Network/Finite Element Hybrid Model. CoRR abs/2307.02349 (2023) - [i18]Dimitrios Loukrezis, Eric Diehl, Herbert De Gersem:
Multivariate sensitivity adaptive polynomial chaos expansion for vector valued surrogate modeling. CoRR abs/2310.09871 (2023) - 2022
- [j2]Katiana Kontolati, Dimitrios Loukrezis, Dimitrios G. Giovanis, Lohit Vandanapu, Michael D. Shields:
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems. J. Comput. Phys. 464: 111313 (2022) - [i17]Katiana Kontolati, Dimitrios Loukrezis, Dimitrios G. Giovanis, Lohit Vandanapu, Michael D. Shields:
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems. CoRR abs/2202.04648 (2022) - [i16]Ion Gabriel Ion, Dimitrios Loukrezis, Herbert De Gersem:
Tensor train based isogeometric analysis for PDE approximation on parameter dependent geometries. CoRR abs/2204.02843 (2022) - [i15]Dimitrios Loukrezis, Herbert De Gersem:
Power Module Heat Sink Design Optimization with Data-Driven Polynomial Chaos Surrogate Models. CoRR abs/2205.08746 (2022) - [i14]Armin Galetzka, Dimitrios Loukrezis, Niklas Georg, Herbert De Gersem, Ulrich Römer:
An hp-adaptive multi-element stochastic collocation method for surrogate modeling with information re-use. CoRR abs/2206.14435 (2022) - [i13]Eric Diehl, Moritz von Tresckow, Lou Scholtissek, Dimitrios Loukrezis, Nicolas Marsic, Wolfgang F. O. Müller, Herbert De Gersem:
Quadrupole Magnet Design based on Genetic Multi-Objective Optimization. CoRR abs/2211.09580 (2022) - 2021
- [i12]Ion Gabriel Ion, Christian Wildner, Dimitrios Loukrezis, Heinz Koeppl, Herbert De Gersem:
Tensor-train approximation of the chemical master equation and its application for parameter inference. CoRR abs/2106.15188 (2021) - [i11]Katiana Kontolati, Dimitrios Loukrezis, Ketson R. M. dos Santos, Dimitrios G. Giovanis, Michael D. Shields:
Manifold learning-based polynomial chaos expansions for high-dimensional surrogate models. CoRR abs/2107.09814 (2021) - [i10]Armin Galetzka, Dimitrios Loukrezis, Herbert De Gersem:
Three-Dimensional Data-Driven Electromagnetic Field Simulation using Real World Measurement Data. CoRR abs/2107.14604 (2021) - [i9]Moritz von Tresckow, Stefan Kurz, Herbert De Gersem, Dimitrios Loukrezis:
A Neural Solver for Variational Problems on CAD Geometries with Application to Electric Machine Simulation. CoRR abs/2111.09005 (2021) - 2020
- [j1]Dimitrios Loukrezis, Herbert De Gersem:
Approximation and Uncertainty Quantification of Systems with Arbitrary Parameter Distributions Using Weighted Leja Interpolation. Algorithms 13(3): 51 (2020) - [i8]Herbert De Gersem, Armin Galetzka, Ion Gabriel Ion, Dimitrios Loukrezis, Ulrich Römer:
Magnetic Field Simulation with Data-Driven Material Modeling. CoRR abs/2002.03715 (2020) - [i7]Armin Galetzka, Dimitrios Loukrezis, Herbert De Gersem:
Data-Driven Solvers for Strongly Nonlinear Material Response. CoRR abs/2008.08482 (2020)
2010 – 2019
- 2019
- [i6]Dimitrios Loukrezis, Herbert De Gersem:
Approximation and Uncertainty Quantification of Stochastic Systems with Arbitrary Input Distributions using Weighted Leja Interpolation. CoRR abs/1904.07709 (2019) - [i5]Dimitrios Loukrezis, Herbert De Gersem:
Adaptive Sparse Polynomial Chaos Expansions via Leja Interpolation. CoRR abs/1911.08312 (2019) - [i4]Dimitrios Loukrezis, Armin Galetzka, Herbert De Gersem:
Robust Adaptive Least Squares Polynomial Chaos Expansions in High-Frequency Applications. CoRR abs/1912.07725 (2019) - 2018
- [i3]Niklas Georg, Dimitrios Loukrezis, Ulrich Römer, Sebastian Schöps:
Uncertainty quantification for an optical grating coupler with an adjoint-based Leja adaptive collocation method. CoRR abs/1807.07485 (2018) - 2017
- [i2]Dimitrios Loukrezis, Ulrich Römer, Herbert De Gersem:
Numerical Comparison of Leja and Clenshaw-Curtis Dimension-Adaptive Collocation for Stochastic Parametric Electromagnetic Field Problems. CoRR abs/1712.07223 (2017) - 2016
- [i1]Dimitrios Loukrezis, Ulrich Römer, Thorben Casper, Sebastian Schöps, Herbert De Gersem:
High Dimensional Uncertainty Quantification for an Electrothermal Field Problem using Stochastic Collocation on Sparse Grids and Tensor Train Decomposition. CoRR abs/1610.03863 (2016)
Coauthor Index
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last updated on 2024-10-16 20:33 CEST by the dblp team
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