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In this paper, we propose a new neural network architecture based on the H2matrix. Even though networks with H2-inspired architecture already exist, andour approach is designed to reduce memory costs and improve performance bytaking into account the sparsity template of the H2 matrix. In numericalcomparison with alternative neural networks, including the known H2-based ones,our architecture showed itself as beneficial in terms of performance, memory,and scalability.

FMM-Net: neural network architecture based on the Fast Multipole Method