Dataflow Matrix Machines as a Model of Computations with Linear Streams
arXiv:1706.00648
Abstract
We overview dataflow matrix machines as a Turing complete generalization of recurrent neural networks and as a programming platform. We describe vector space of finite prefix trees with numerical leaves which allows us to combine expressive power of dataflow matrix machines with simplicity of traditional recurrent neural networks.
6 pages, accepted for presentation at LearnAut 2017: Learning and Automata workshop at LICS (Logic in Computer Science) 2017 conference. Preprint original version: April 9, 2017; minor correction: May 1, 2017