Dataflow Matrix Machines as a Generalization of Recurrent Neural Networks

03/29/2016

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by   Michael Bukatin, et al.

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Dataflow matrix machines are a powerful generalization of recurrent neural networks. They work with multiple types of arbitrary linear streams, multiple types of powerful neurons, and allow to incorporate higher-order constructions. We expect them to be useful in machine learning and probabilistic programming, and in the synthesis of dynamic systems and of deterministic and probabilistic programs.