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arXiv · 1603.09002

Dataflow Matrix Machines as a Generalization of Recurrent Neural Networks

Michael Bukatin·Steve Matthews·Andrey Radul
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Abstract

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.

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Michael Bukatin, Steve Matthews, Andrey Radul. 2016-03-29. Dataflow Matrix Machines as a Generalization of Recurrent Neural Networks. https://arxiv.org/abs/1603.09002

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