论文标题
FMM-NET：基于快速多极方法的神经网络体系结构
FMM-Net: neural network architecture based on the Fast Multipole Method
论文作者
论文摘要
在本文中，我们提出了一种基于H2矩阵的新神经网络体系结构。即使已经存在具有H2启发架构的网络，并且我们的方法旨在通过考虑H2矩阵的稀疏模板来降低内存成本并提高性能。在与替代神经网络（包括已知基于H2的神经网络）的数值比较中，我们的体系结构在性能，记忆和可扩展性方面表现出了有益的。
In this paper, we propose a new neural network architecture based on the H2 matrix. Even though networks with H2-inspired architecture already exist, and our approach is designed to reduce memory costs and improve performance by taking into account the sparsity template of the H2 matrix. In numerical comparison with alternative neural networks, including the known H2-based ones, our architecture showed itself as beneficial in terms of performance, memory, and scalability.
