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In recent years, deep learning has led to impressive results in many fields. In this paper, we introduce a multiscale artificial neural network for high-dimensional nonlinear maps based on the idea of hierarchical nested bases in the fast multipole method and the $$\mathcal {H}^2$$ H2 -matrices. This approach allows us to efficiently approximate discretized nonlinear maps arising from partial differential...