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From the 1 of 5 linked papers with an AI index.

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5 papers

math.NA2026

Graph Neural Multilevel Preconditioners for Iterative Solvers

Zechen Zhang, Rui Peng Li, Yousef Saad

The paper proposes a Graph Neural Multilevel Preconditioner that integrates an algebraic multigrid hierarchy into a learned GNN framework to improve the convergence of iterative so…

math.NA2026

Factored Sparse Approximate Inverse Preconditioning via Spectral Optimization

Francesco Brarda, Tianshi Xu, Vassilis Kalantzis +2

In this paper, we study value selection for fixed-pattern factorized sparse approximate inverse preconditioners. Given a prescribed sparsity pattern for a factor we choose its…

math.NA2026

Hybrid Digital-Analog Approximate Inverse Preconditioning for Krylov Methods

Shikhar Shah, Rui Peng Li, Tayfun Gokmen +3

Analog in-memory computing enables highly parallel matrix-vector multiplications with reduced data movement, but the resulting operations are noisy, quantized, and affected by devi…

cs.CE2026

Generative modeling of granular flow on inclined planes using conditional flow matching

Xuyang Li, Rui Li, Teng Man +1

Granular flows govern many natural and industrial processes, yet their interior kinematics and mechanics remain largely unobservable, as experiments access only boundaries or free…

math.NA2025

Neural Approximate Inverse Preconditioners

Tianshi Xu, Rui Peng Li, Yuanzhe Xi

In this paper, we propose a data-driven framework for constructing efficient approximate inverse preconditioners for elliptic partial differential equations (PDEs) by learning the…