Alexander Heinlein

63 papers A 1Journal 57Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Are Deep Learning Based Hybrid PDE Solvers Reliable? Why Training Paradigms and Update Strategies Matter. CoRR Yuhan Wu, Jan Willem van Beek, Victorita Dolean, Alexander Heinlein
2026	J	`jnl`	Multi-Preconditioned LBFGS for Training Finite-Basis PINNs. CoRR Marc Salvadó-Benasco, Aymane Kssim, Alexander Heinlein, Rolf Krause, Serge Gratton, Alena Kopanicáková
2026	J	`jnl`	The Error of Deep Operator Networks Is the Sum of Its Parts: Branch-Trunk and Mode Error Decompositions. CoRR Alexander Heinlein, Johannes Taraz
2025	J	`jnl`	Algebraic Construction of Adaptive Coarse Spaces for Two-Level Schwarz Preconditioners. SIAM J. Sci. Comput. Alexander Heinlein, Kathrin Smetana
2025	J	`jnl`	Conformalized-KANs: Uncertainty Quantification with Coverage Guarantees for Kolmogorov-Arnold Networks (KANs) in Scientific Machine Learning. CoRR Amirhossein Mollaali, Christian B. Moya, Amanda A. Howard, Alexander Heinlein, Panos Stinis, Guang Lin
2025	J	`jnl`	Coupling deal.II and FROSch: A Sustainable and Accessible (O)RAS Preconditioner. ACM Trans. Math. Softw. Sebastian Kinnewig, Alexander Heinlein, Thomas Wick
2025	J	`jnl`	DDU-Net: A Domain Decomposition-Based CNN for High-Resolution Image Segmentation on Multiple GPUs. IEEE Access Corné Verburg, Alexander Heinlein, Eric C. Cyr
2025	J	`jnl`	Domain decomposition architectures and Gauss-Newton training for physics-informed neural networks. CoRR Alexander Heinlein, Taniya Kapoor
2025	J	`jnl`	Domain-Decomposed Graph Neural Network Surrogate Modeling for Ice Sheets. CoRR Adrienne M. Propp, Mauro Perego, Eric C. Cyr, Anthony Gruber, Amanda A. Howard, Alexander Heinlein, Panos Stinis, Daniel M. Tartakovsky
2025	J	`jnl`	Few-Shot Learning by Explicit Physics Integration: An Application to Groundwater Heat Transport. CoRR Julia Pelzer, Corné Verburg, Alexander Heinlein, Miriam Schulte
2025	J	`jnl`	Improving pseudo-time stepping convergence for CFD simulations with neural networks. Comput. Math. Appl. Anouk Zandbergen, Tycho van Noorden, Alexander Heinlein
2025	J	`jnl`	Learning the solution operator of two-dimensional incompressible Navier-Stokes equations using physics-aware convolutional neural networks. J. Comput. Phys. Viktor Grimm, Alexander Heinlein, Axel Klawonn
2025	J	`jnl`	Monolithic and Block Overlapping Schwarz Preconditioners for the Incompressible Navier-Stokes Equations. CoRR Alexander Heinlein, Axel Klawonn, Jascha Knepper, Lea Sassmannshausen
2025	J	`jnl`	Numerical study on hyper parameter settings for neural network approximation to partial differential equations. CoRR Hee Jun Yang, Alexander Heinlein, Hyea Hyun Kim
2025	J	`jnl`	Sharpened PCG Iteration Bound for High-Contrast Heterogeneous Scalar Elliptic PDEs. CoRR Philip Soliman, Filipe Cumaru, Alexander Heinlein
2025	J	`jnl`	Trilinos: Enabling Scientific Computing Across Diverse Hardware Architectures at Scale. CoRR 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, Jonathan J. Hu, Brian Michael Kelley, Kyungjoo Kim, Drew P. Kouri, Paul Kuberry, Kim Liegeois, Curtis C. Ober, Roger P. Pawlowski, Carl Pearson, Mauro Perego, Eric T. Phipps, Denis Ridzal, Nathan V. Roberts, Christopher M. Siefert, Heidi Thornquist, Romin Tomasetti, Christian R. Trott, Raymond S. Tuminaro, James M. Willenbring, Michael M. Wolf, Ichitaro Yamazaki
2025	J	`jnl`	Two-level additive Schwarz preconditioners for reduced integration methods. CoRR Filipe Cumaru, Alexander Heinlein, Joachim Schöberl
2024	J	`jnl`	A computational study of algebraic coarse spaces for two-level overlapping additive Schwarz preconditioners. CoRR Filipe A. C. S. Alves, Alexander Heinlein, Hadi Hajibeygi
2024	J	`jnl`	Coarse Spaces Based on Higher-Order Interpolation for Schwarz Preconditioners for Helmholtz Problems. CoRR Erik Sieburgh, Alexander Heinlein, Vandana Dwarka, Cornelis Vuik
2024	J	`jnl`	Coupling deal.II and FROSch: A Sustainable and Accessible (O)RAS Preconditioner. CoRR Alexander Heinlein, Sebastian Kinnewig, Thomas Wick
2024	J	`jnl`	DDU-Net: A Domain Decomposition-based CNN for High-Resolution Image Segmentation on Multiple GPUs. CoRR Corné Verburg, Alexander Heinlein, Eric C. Cyr
2024	J	`jnl`	Deep operator network models for predicting post-burn contraction. CoRR Selma Husanovic, Ginger Egberts, Alexander Heinlein, Fred J. Vermolen
2024	J	`jnl`	Finite basis Kolmogorov-Arnold networks: domain decomposition for data-driven and physics-informed problems. CoRR Amanda A. Howard, Bruno Jacob, Sarah H. Murphy, Alexander Heinlein, Panos Stinis
2024	J	`jnl`	High-order discretized ACMS method for the simulation of finite-size two-dimensional photonic crystals. CoRR Elena Giammatteo, Alexander Heinlein, Philip Lukas Lederer, Matthias Schlottbom
2024	J	`jnl`	Multifidelity domain decomposition-based physics-informed neural networks for time-dependent problems. CoRR Alexander Heinlein, Amanda A. Howard, Damien Beecroft, Panos Stinis
2024	J	`jnl`	Nonlinear Two-Level Schwarz Methods: A Parallel Implementation in FROSch. CoRR Alexander Heinlein, Kyrill Ho, Axel Klawonn, Martin Lanser
2024	J	`jnl`	Overlapping Schwarz Preconditioners for Randomized Neural Networks with Domain Decomposition. CoRR Yong Shang, Alexander Heinlein, Siddhartha Mishra, Fei Wang
2024	J	`jnl`	PACMANN: Point Adaptive Collocation Method for Artificial Neural Networks. CoRR Coen Visser, Alexander Heinlein, Bianca Giovanardi
2024	J	`jnl`	Towards Graph Neural Network Surrogates Leveraging Mechanistic Expert Knowledge for Pandemic Response. CoRR Agatha Schmidt, Henrik Zunker, Alexander Heinlein, Martin J. Kühn
2024	J	`jnl`	Towards Model Discovery Using Domain Decomposition and PINNs. CoRR Tirtho S. Saha, Alexander Heinlein, Cordula Reisch
2024	J	`jnl`	Two-level deep domain decomposition method. CoRR Victorita Dolean, Serge Gratton, Alexander Heinlein, Valentin Mercier
2023	J	`jnl`	A Comparison Of Direct Solvers In FROSch Applied To Chemo-Mechanics. CoRR Alexander Heinlein, Björn Kiefer, Stefan Prüger, Oliver Rheinbach, Friederike Röver
2023	J	`jnl`	A Multilevel Extension of the GDSW Overlapping Schwarz Preconditioner in Two Dimensions. Comput. Methods Appl. Math. Alexander Heinlein, Oliver Rheinbach, Friederike Röver
2023	J	`jnl`	A computational framework for pharmaco-mechanical interactions in arterial walls using parallel monolithic domain decomposition methods. CoRR Daniel Balzani, Alexander Heinlein, Axel Klawonn, Jascha Knepper, Sharan Nurani Ramesh, Oliver Rheinbach, Lea Sassmannshausen, Klemens Uhlmann
2023	J	`jnl`	Adaptive Nonlinear Domain Decomposition Methods with an Application to the $p$-Laplacian. SIAM J. Sci. Comput. Alexander Heinlein, Axel Klawonn, Martin Lanser
2023	J	`jnl`	An Experimental Study of Two-Level Schwarz Domain Decomposition Preconditioners on GPUs. CoRR Ichitaro Yamazaki, Alexander Heinlein, Sivasankaran Rajamanickam
2023	A	`conf`	An Experimental Study of Two-level Schwarz Domain-Decomposition Preconditioners on GPUs. IPDPS Ichitaro Yamazaki, Alexander Heinlein, Sivasankaran Rajamanickam
2023	J	`jnl`	An extension of the approximate component mode synthesis method to the heterogeneous Helmholtz equation. CoRR Elena Giammatteo, Alexander Heinlein, Matthias Schlottbom
2023	J	`jnl`	Improving Pseudo-Time Stepping Convergence for CFD Simulations With Neural Networks. CoRR Anouk Zandbergen, Tycho van Noorden, Alexander Heinlein
2023	J	`jnl`	Learning the solution operator of two-dimensional incompressible Navier-Stokes equations using physics-aware convolutional neural networks. CoRR Viktor Grimm, Alexander Heinlein, Axel Klawonn
2023	J	`jnl`	Machine learning for phase-resolved reconstruction of nonlinear ocean wave surface elevations from sparse remote sensing data. CoRR Svenja Ehlers, Marco Klein, Alexander Heinlein, Mathies Wedler, Nicolas Desmars, Norbert P. Hoffmann, Merten Stender
2023	J	`jnl`	Multilevel domain decomposition-based architectures for physics-informed neural networks. CoRR Victorita Dolean, Alexander Heinlein, Siddhartha Mishra, Ben Moseley
2023	J	`jnl`	Parallel Scalability of Three-Level FROSch Preconditioners to 220000 Cores using the Theta Supercomputer. SIAM J. Sci. Comput. Alexander Heinlein, Oliver Rheinbach, Friederike Röver
2023	J	`jnl`	Towards parallel time-stepping for the numerical simulation of atherosclerotic plaque growth. J. Comput. Phys. Stefan Frei, Alexander Heinlein
2022	J	`jnl`	A fully algebraic and robust two-level Schwarz method based on optimal local approximation spaces. CoRR Alexander Heinlein, Kathrin Smetana
2022	J	`jnl`	Adaptive GDSW Coarse Spaces of Reduced Dimension for Overlapping Schwarz Methods. SIAM J. Sci. Comput. Alexander Heinlein, Axel Klawonn, Jascha Knepper, Oliver Rheinbach, Olof B. Widlund
2022	J	`jnl`	Efficient coarse correction for parallel time-stepping in plaque growth simulations. CoRR Stefan Frei, Alexander Heinlein
2022	J	`jnl`	FROSch Preconditioners for Land Ice Simulations of Greenland and Antarctica. SIAM J. Sci. Comput. Alexander Heinlein, Mauro Perego, Sivasankaran Rajamanickam
2022	J	`jnl`	Finite basis physics-informed neural networks as a Schwarz domain decomposition method. CoRR Victorita Dolean, Alexander Heinlein, Siddhartha Mishra, Ben Moseley
2022	J	`jnl`	Towards parallel time-stepping for the numerical simulation of atherosclerotic plaque growth. CoRR Stefan Frei, Alexander Heinlein
2021	J	`jnl`	Combining Machine Learning and Adaptive Coarse Spaces - A Hybrid Approach for Robust FETI-DP Methods in Three Dimensions. SIAM J. Sci. Comput. Alexander Heinlein, Axel Klawonn, Martin Lanser, Janine Weber
2021	J	`jnl`	On temporal homogenization in the numerical simulation of atherosclerotic plaque growth. CoRR Stefan Frei, Alexander Heinlein, Thomas Richter
2020	J	`jnl`	Additive and Hybrid Nonlinear Two-Level Schwarz Methods and Energy Minimizing Coarse Spaces for Unstructured Grids. SIAM J. Sci. Comput. Alexander Heinlein, Martin Lanser
2019	J	`jnl`	Adaptive GDSW Coarse Spaces for Overlapping Schwarz Methods in Three Dimensions. SIAM J. Sci. Comput. Alexander Heinlein, Axel Klawonn, Jascha Knepper, Oliver Rheinbach
2019	—	`conf`	Fully Algebraic Two-Level Overlapping Schwarz Preconditioners for Elasticity Problems. ENUMATH Alexander Heinlein, Christian Hochmuth, Axel Klawonn
2019	J	`jnl`	Machine Learning in Adaptive Domain Decomposition Methods - Predicting the Geometric Location of Constraints. SIAM J. Sci. Comput. Alexander Heinlein, Axel Klawonn, Martin Lanser, Janine Weber
2019	—	`conf`	Machine Learning in Adaptive FETI-DP: Reducing the Effort in Sampling. ENUMATH Alexander Heinlein, Axel Klawonn, Martin Lanser, Janine Weber
2019	J	`jnl`	Monolithic Overlapping Schwarz Domain Decomposition Methods with GDSW Coarse Spaces for Incompressible Fluid Flow Problems. SIAM J. Sci. Comput. Alexander Heinlein, Christian Hochmuth, Axel Klawonn
2019	—	`conf`	Stationary Flow Predictions Using Convolutional Neural Networks. ENUMATH Matthias Eichinger, Alexander Heinlein, Axel Klawonn
2016	J	`jnl`	A Parallel Implementation of a Two-Level Overlapping Schwarz Method with Energy-Minimizing Coarse Space Based on Trilinos. SIAM J. Sci. Comput. Alexander Heinlein, Axel Klawonn, Oliver Rheinbach
2016	—	`—`	Parallel Overlapping Schwarz Preconditioners and Multiscale Discretizations with Applications to Fluid-Structure Interaction and Highly Heterogeneous Problems Alexander Heinlein
2015	—	`conf`	Parallel Two-Level Overlapping Schwarz Methods in Fluid-Structure Interaction. ENUMATH Alexander Heinlein, Axel Klawonn, Oliver Rheinbach
2015	J	`jnl`	The approximate component mode synthesis special finite element method in two dimensions: Parallel implementation and numerical results. J. Comput. Appl. Math. Alexander Heinlein, Ulrich Hetmaniuk, Axel Klawonn, Oliver Rheinbach