most citedBlockAMC: Scalable In-Memory Analog Matrix Computing for Solving Linear Systems

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math.NA2023

Reducing operator complexity in Algebraic Multigrid with Machine Learning Approaches

Ru Huang, Kai Chang, Huan He +2

We propose a data-driven and machine-learning-based approach to compute non-Galerkin coarse-grid operators in algebraic multigrid (AMG) methods, addressing the well-known issue of…