A learned interface-aware neural Newton preconditioner improves convergence on difficult CZM increments while preserving the original discrete solution set and force-displacement response.
Lee, et al., A neural-operator preconditioned newton method, arXiv preprint arXiv:2511.08811 (2025)
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McMg is a phase-space multi-channel multigrid preconditioner that maps residuals to corrections while retaining unresolved wave information in extra channels, showing fewer iterations and lower runtime than classical and neural baselines on high-wavenumber 3D Helmholtz problems.
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Interface-Aware Neural Newton Preconditioning for Robust Cohesive Zone Model Simulations
A learned interface-aware neural Newton preconditioner improves convergence on difficult CZM increments while preserving the original discrete solution set and force-displacement response.
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McMg: A Learned Phase-Space Multi-channel Multigrid Preconditioner for Helmholtz Equation
McMg is a phase-space multi-channel multigrid preconditioner that maps residuals to corrections while retaining unresolved wave information in extra channels, showing fewer iterations and lower runtime than classical and neural baselines on high-wavenumber 3D Helmholtz problems.