Recurrent Network Structure for Computing Quasi-inverses of the Sierpinski Space-Filling Curves

This paper deals with the design of the recurrent neural network structure approximating the quasi-inverses of the multi-dimensional Sierpinski space-filling curves. The network consists of two subsequent recurrent layers. The network structure shows that computing the quasi-inverse of the Sierpinski space-filling curve can be performed massively parallel.

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