Parallel Two-Level Overlapping Schwarz Methods in Fluid-Structure Interaction. - Alexander Heinlein; Axel Klawonn; Oliver Rheinbach (ENUMATH, 2015)

The approximate component mode synthesis special finite element method in two dimensions: Parallel implementation and numerical results. - Alexander Heinlein; Ulrich Hetmaniuk; Axel Klawonn; Oliver Rheinbach (J. Comput. Appl. Math., 2015)

A Parallel Implementation of a Two-Level Overlapping Schwarz Method with Energy-Minimizing Coarse Space Based on Trilinos. - Alexander Heinlein; Axel Klawonn; Oliver Rheinbach (SIAM J. Sci. Comput., 2016)

Parallel Overlapping Schwarz Preconditioners and Multiscale Discretizations with Applications to Fluid-Structure Interaction and Highly Heterogeneous Problems - Alexander Heinlein (2016)

Stationary Flow Predictions Using Convolutional Neural Networks. - Matthias Eichinger; Alexander Heinlein; Axel Klawonn (ENUMATH, 2019)

Fully Algebraic Two-Level Overlapping Schwarz Preconditioners for Elasticity Problems. - Alexander Heinlein; Christian Hochmuth; Axel Klawonn (ENUMATH, 2019)

Machine Learning in Adaptive FETI-DP: Reducing the Effort in Sampling. - Alexander Heinlein; Axel Klawonn; Martin Lanser; Janine Weber (ENUMATH, 2019)

Monolithic Overlapping Schwarz Domain Decomposition Methods with GDSW Coarse Spaces for Incompressible Fluid Flow Problems. - Alexander Heinlein; Christian Hochmuth; Axel Klawonn (SIAM J. Sci. Comput., 2019)

Adaptive GDSW Coarse Spaces for Overlapping Schwarz Methods in Three Dimensions. - Alexander Heinlein; Axel Klawonn; Jascha Knepper; Oliver Rheinbach (SIAM J. Sci. Comput., 2019)

Machine Learning in Adaptive Domain Decomposition Methods - Predicting the Geometric Location of Constraints. - Alexander Heinlein; Axel Klawonn; Martin Lanser; Janine Weber (SIAM J. Sci. Comput., 2019)

Additive and Hybrid Nonlinear Two-Level Schwarz Methods and Energy Minimizing Coarse Spaces for Unstructured Grids. - Alexander Heinlein; Martin Lanser (SIAM J. Sci. Comput., 2020)

On temporal homogenization in the numerical simulation of atherosclerotic plaque growth. - Stefan Frei; Alexander Heinlein; Thomas Richter 003 (CoRR, 2021)

Combining Machine Learning and Adaptive Coarse Spaces - A Hybrid Approach for Robust FETI-DP Methods in Three Dimensions. - Alexander Heinlein; Axel Klawonn; Martin Lanser; Janine Weber (SIAM J. Sci. Comput., 2021)

Efficient coarse correction for parallel time-stepping in plaque growth simulations. - Stefan Frei; Alexander Heinlein (CoRR, 2022)

A fully algebraic and robust two-level Schwarz method based on optimal local approximation spaces. - Alexander Heinlein; Kathrin Smetana (CoRR, 2022)

Finite basis physics-informed neural networks as a Schwarz domain decomposition method. - Victorita Dolean; Alexander Heinlein; Siddhartha Mishra; Ben Moseley (CoRR, 2022)

Adaptive GDSW Coarse Spaces of Reduced Dimension for Overlapping Schwarz Methods. - Alexander Heinlein; Axel Klawonn; Jascha Knepper; Oliver Rheinbach; Olof B. Widlund (SIAM J. Sci. Comput., 2022)

FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica. - Alexander Heinlein; Mauro Perego; Sivasankaran Rajamanickam (SIAM J. Sci. Comput., 2022)

An Experimental Study of Two-level Schwarz Domain-Decomposition Preconditioners on GPUs. - Ichitaro Yamazaki; Alexander Heinlein; Sivasankaran Rajamanickam (IPDPS, 2023)

An extension of the approximate component mode synthesis method to the heterogeneous Helmholtz equation. - Elena Giammatteo; Alexander Heinlein; Matthias Schlottbom (CoRR, 2023)

Machine learning for phase-resolved reconstruction of nonlinear ocean wave surface elevations from sparse remote sensing data. - Svenja Ehlers; Marco Klein; Alexander Heinlein; Mathies Wedler; Nicolas Desmars; Norbert P. Hoffmann; Merten Stender (CoRR, 2023)

Multilevel domain decomposition-based architectures for physics-informed neural networks. - Victorita Dolean; Alexander Heinlein; Siddhartha Mishra; Ben Moseley (CoRR, 2023)

A computational framework for pharmaco-mechanical interactions in arterial walls using parallel monolithic domain decomposition methods. - Daniel Balzani; Alexander Heinlein; Axel Klawonn; Jascha Knepper; Sharan Nurani Ramesh; Oliver Rheinbach; Lea Sassmannshausen; Klemens Uhlmann (CoRR, 2023)

A Comparison Of Direct Solvers In FROSch Applied To Chemo-Mechanics. - Alexander Heinlein; Björn Kiefer; Stefan Prüger; Oliver Rheinbach; Friederike Röver (CoRR, 2023)

Adaptive Nonlinear Domain Decomposition Methods with an Application to the $p$-Laplacian. - Alexander Heinlein; Axel Klawonn; Martin Lanser (SIAM J. Sci. Comput., 2023)

Parallel Scalability of Three-Level FROSch Preconditioners to 220000 Cores using the Theta Supercomputer. - Alexander Heinlein; Oliver Rheinbach; Friederike Röver (SIAM J. Sci. Comput., 2023)

A Multilevel Extension of the GDSW Overlapping Schwarz Preconditioner in Two Dimensions. - Alexander Heinlein; Oliver Rheinbach; Friederike Röver (Comput. Methods Appl. Math., 2023)

Towards parallel time-stepping for the numerical simulation of atherosclerotic plaque growth. - Stefan Frei; Alexander Heinlein (J. Comput. Phys., 2023)

Multifidelity domain decomposition-based physics-informed neural networks for time-dependent problems. - Alexander Heinlein; Amanda A. Howard; Damien Beecroft; Panos Stinis (CoRR, 2024)

Finite basis Kolmogorov-Arnold networks: domain decomposition for data-driven and physics-informed problems. - Amanda A. Howard; Bruno Jacob; Sarah H. Murphy; Alexander Heinlein; Panos Stinis (CoRR, 2024)

Coarse Spaces Based on Higher-Order Interpolation for Schwarz Preconditioners for Helmholtz Problems. - Erik Sieburgh; Alexander Heinlein; Vandana Dwarka; Cornelis Vuik (CoRR, 2024)

A computational study of algebraic coarse spaces for two-level overlapping additive Schwarz preconditioners. - Filipe A. C. S. Alves; Alexander Heinlein; Hadi Hajibeygi (CoRR, 2024)

Two-level deep domain decomposition method. - Victorita Dolean; Serge Gratton; Alexander Heinlein; Valentin Mercier (CoRR, 2024)

Towards Model Discovery Using Domain Decomposition and PINNs. - Tirtho S. Saha; Alexander Heinlein; Cordula Reisch (CoRR, 2024)

High-order discretized ACMS method for the simulation of finite-size two-dimensional photonic crystals. - Elena Giammatteo; Alexander Heinlein; Philip Lukas Lederer; Matthias Schlottbom (CoRR, 2024)

Coupling deal.II and FROSch: A Sustainable and Accessible (O)RAS Preconditioner. - Alexander Heinlein; Sebastian Kinnewig; Thomas Wick (CoRR, 2024)

Nonlinear Two-Level Schwarz Methods: A Parallel Implementation in FROSch. - Alexander Heinlein; Kyrill Ho; Axel Klawonn; Martin Lanser (CoRR, 2024)

Towards Graph Neural Network Surrogates Leveraging Mechanistic Expert Knowledge for Pandemic Response. - Agatha Schmidt; Henrik Zunker; Alexander Heinlein; Martin J. Kühn (CoRR, 2024)

Deep operator network models for predicting post-burn contraction. - Selma Husanovic; Ginger Egberts; Alexander Heinlein; Fred J. Vermolen (CoRR, 2024)

PACMANN: Point Adaptive Collocation Method for Artificial Neural Networks. - Coen Visser; Alexander Heinlein; Bianca Giovanardi (CoRR, 2024)

Overlapping Schwarz Preconditioners for Randomized Neural Networks with Domain Decomposition. - Yong Shang; Alexander Heinlein; Siddhartha Mishra; Fei Wang (CoRR, 2024)

DDU-Net: A Domain Decomposition-Based CNN for High-Resolution Image Segmentation on Multiple GPUs. - Corné Verburg; Alexander Heinlein; Eric C. Cyr (IEEE Access, 2025)

Improving pseudo-time stepping convergence for CFD simulations with neural networks. - Anouk Zandbergen; Tycho van Noorden; Alexander Heinlein (Comput. Math. Appl., 2025)

Learning the solution operator of two-dimensional incompressible Navier-Stokes equations using physics-aware convolutional neural networks. - Viktor Grimm; Alexander Heinlein; Axel Klawonn (J. Comput. Phys., 2025)

Algebraic Construction of Adaptive Coarse Spaces for Two-Level Schwarz Preconditioners. - Alexander Heinlein; Kathrin Smetana (SIAM J. Sci. Comput., 2025)

Trilinos: Enabling Scientific Computing Across Diverse Hardware Architectures at Scale. - Matthias Mayr; Alexander Heinlein; Christian A. Glusa; Siva Rajamanickam; Maarten Arnst; Roscoe A. Bartlett; Luc Berger-Vergiat; Erik G. Boman; Karen D. Devine; Graham Harper; Michael A. Heroux; Mark Hoemmen; et al. (CoRR, 2025)

Numerical study on hyper parameter settings for neural network approximation to partial differential equations. - Hee Jun Yang; Alexander Heinlein; Hyea Hyun Kim (CoRR, 2025)

Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning. - Amirhossein Mollaali; Christian B. Moya; Amanda A. Howard; Alexander Heinlein; Panos Stinis; Guang Lin 001 (CoRR, 2025)

Monolithic and Block Overlapping Schwarz Preconditioners for the Incompressible Navier-Stokes Equations. - Alexander Heinlein; Axel Klawonn; Jascha Knepper; Lea Sassmannshausen (CoRR, 2025)

Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport. - Julia Pelzer; Corné Verburg; Alexander Heinlein; Miriam Schulte (CoRR, 2025)