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Articles by Martin Eigel | Synthical
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Martin Eigel
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21
Functional SDE approximation inspired by a deep operator network architecture
21 May 2025 by
Martin Eigel
and
Charles Miranda
Numerical Analysis
,
Machine Learning
Multi-level Neural Networks for high-dimensional parametric obstacle problems
7 April 2025 by
Martin Eigel
and
others
Machine Learning
,
Numerical Analysis
A convergent adaptive finite element stochastic Galerkin method based on multilevel expansions of random fields
27 March 2025 by
Markus Bachmayr
and
others
Numerical Analysis
Large-scale stochastic simulation of open quantum systems
29 January 2025 by
Aaron Sander
and
others
Quantum Physics
,
Other Condensed Matter
Sampling from Boltzmann densities with physics informed low-rank formats
10 December 2024 by
Paul Hagemann
and
others
Machine Learning
,
Optimization and Control
Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures
10 December 2024 by
Charles Miranda
and
others
Machine Learning
,
Probability
An Eulerian approach to regularized JKO scheme with low-rank tensor decompositions for Bayesian inversion
19 November 2024 by
Vitalii Aksenov
and
Martin Eigel
Numerical Analysis
,
Optimization and Control
Generative modeling with low-rank Wasserstein polynomial chaos expansions
16 October 2024 by
Robert Gruhlke
and
Martin Eigel
Numerical Analysis
,
Probability
Multilevel CNNs for Parametric PDEs based on Adaptive Finite Elements
20 August 2024 by
Janina Enrica Schütte
and
Martin Eigel
Machine Learning
,
Numerical Analysis
On the convergence of adaptive Galerkin FEM for parametric PDEs with lognormal coefficients
26 July 2024 by
Martin Eigel
and
Nando Hegemann
Numerical Analysis
Adaptive Multilevel Neural Networks for Parametric PDEs with Error Estimation
19 March 2024 by
Janina Schutte
and
Martin Eigel
Numerical Analysis
,
Machine Learning
Generative Modelling with Tensor Train approximations of Hamilton--Jacobi--Bellman equations
23 February 2024 by
David Sommer
and
others
Machine Learning
,
Statistics Theory
Weighted sparsity and sparse tensor networks for least squares approximation
13 October 2023 by
Philipp Trunschke
and
others
Numerical Analysis
Multilevel CNNs for Parametric PDEs
4 April 2023 by
Cosmas Heiß
and
others
Machine Learning
,
Numerical Analysis
Less interaction with forward models in Langevin dynamics
22 December 2022 by
Martin Eigel
and
others
Numerical Analysis
,
Dynamical Systems
Adaptive non-intrusive reconstruction of solutions to high-dimensional parametric PDEs
26 October 2022 by
Martin Eigel
and
others
Numerical Analysis
,
Functional Analysis
Efficient approximation of high-dimensional exponentials by tensornetworks
18 July 2022 by
Martin Eigel
and
others
Numerical Analysis
,
Dynamical Systems
Dynamical low-rank approximations of solutions to the Hamilton-Jacobi-Bellman equation
29 November 2021 by
Martin Eigel
and
others
Optimization and Control
Pricing high-dimensional Bermudan options with hierarchical tensor formats
6 March 2021 by
Christian Bayer
and
others
Computational Finance
,
Computational Engineering, Finance, and Science
On the convergence of adaptive stochastic collocation for elliptic partial differential equations with affine diffusion
10 September 2020 by
Martin Eigel
and
others
Numerical Analysis
Low-rank tensor reconstruction of concentrated densities with application to Bayesian inversion
10 August 2020 by
Martin Eigel
and
others
Numerical Analysis
Convergence bounds for empirical nonlinear least-squares
6 January 2020 by
Martin Eigel
and
others
Numerical Analysis
,
Probability
An adaptive stochastic Galerkin tensor train discretization for randomly perturbed domains
20 February 2019 by
Martin Eigel
and
others
Numerical Analysis
Adaptive stochastic Galerkin FEM for lognormal coefficients in hierarchical tensor representations
1 November 2018 by
Martin Eigel
and
others
Numerical Analysis
Variational Monte Carlo - Bridging Concepts of Machine Learning and High Dimensional Partial Differential Equations
2 October 2018 by
Martin Eigel
and
others
Numerical Analysis
Reproducing kernel Hilbert spaces and variable metric algorithms in PDE constrained shape optimisation
19 April 2016 by
Martin Eigel
and
Kevin Sturm
Optimization and Control
Topics
Numerical Analysis
Machine Learning
Probability
Statistics Theory
Dynamical Systems
Spectral Theory
Optimization and Control
Analysis of PDEs
Functional Analysis
Computational Finance
Computational Engineering, Finance, and Science