Notes on Pure Dataflow Matrix Machines: Programming with Self-referential Matrix Transformations

1 code implementation • 4 Oct 2016 • Michael Bukatin, Steve Matthews, Andrey Radul

Dataflow matrix machines are self-referential generalized recurrent neural nets.

Programming Languages

Programming Patterns in Dataflow Matrix Machines and Generalized Recurrent Neural Nets

1 code implementation • 30 Jun 2016 • Michael Bukatin, Steve Matthews, Andrey Radul

Dataflow matrix machines arise naturally in the context of synchronous dataflow programming with linear streams.

Dataflow matrix machines as programmable, dynamically expandable, self-referential generalized recurrent neural networks

1 code implementation • 17 May 2016 • Michael Bukatin, Steve Matthews, Andrey Radul

Dataflow matrix machines are a powerful generalization of recurrent neural networks.

Dataflow Matrix Machines as a Generalization of Recurrent Neural Networks

1 code implementation • 29 Mar 2016 • Michael Bukatin, Steve Matthews, Andrey Radul

Dataflow matrix machines are a powerful generalization of recurrent neural networks.

BIG-bench Machine Learning Probabilistic Programming

Linear Models of Computation and Program Learning

no code implementations • 15 Dec 2015 • Michael Bukatin, Steve Matthews

We consider two classes of computations which admit taking linear combinations of execution runs: probabilistic sampling and generalized animation.

Probabilistic Programming