Machine Learning in Adaptive FETI-DP: Reducing the Effort in Sampling
From MaRDI portal
Publication:5152855
DOI10.1007/978-3-030-55874-1_58zbMath1475.65213OpenAlexW2994835364MaRDI QIDQ5152855
Martin Lanser, Janine Weber, Axel Klawonn, Alexander Heinlein
Publication date: 27 September 2021
Published in: Lecture Notes in Computational Science and Engineering (Search for Journal in Brave)
Full work available at URL: https://kups.ub.uni-koeln.de/10439/1/CDS_TR-2019-19.pdf
Multigrid methods; domain decomposition for boundary value problems involving PDEs (65N55) Learning and adaptive systems in artificial intelligence (68T05)
Related Items
Learning adaptive coarse basis functions of FETI-DP ⋮ Combining Machine Learning and Adaptive Coarse Spaces---A Hybrid Approach for Robust FETI-DP Methods in Three Dimensions
Cites Work
- Unnamed Item
- Adaptive selection of face coarse degrees of freedom in the BDDC and the FETI-DP iterative substructuring methods
- Multiscale coarse spaces for overlapping Schwarz methods based on the ACMS space in 2D
- Adaptive FETI-DP and BDDC methods with a generalized transformation of basis for heterogeneous problems
- Adaptive BDDC in three dimensions
- Projector preconditioning and transformation of basis in FETI-DP algorithms for contact problems
- Adaptive Coarse Spaces for FETI-DP in Three Dimensions
- Deflation, Projector Preconditioning, and Balancing in Iterative Substructuring Methods: Connections and New Results
- Dual-primal FETI methods for linear elasticity
- An Adaptive GDSW Coarse Space for Two-Level Overlapping Schwarz Methods in Two Dimensions
- Machine Learning in Adaptive Domain Decomposition Methods---Predicting the Geometric Location of Constraints
- Understanding Machine Learning