4 papers · 1 filter
Notes on Pure Dataflow Matrix Machines: Programming with Self-referential Matrix Transformations
Michael Bukatin, Steve Matthews, Andrey Radul
Dataflow matrix machines are self-referential generalized recurrent neural nets. The self-referential mechanism is provided via a stream of matrices defining the connectivity and w…
Programming Patterns in Dataflow Matrix Machines and Generalized Recurrent Neural Nets
Michael Bukatin, Steve Matthews, Andrey Radul
Dataflow matrix machines arise naturally in the context of synchronous dataflow programming with linear streams. They can be viewed as a rather powerful generalization of recurrent…
Dataflow Graphs as Matrices and Programming with Higher-order Matrix Elements
Michael Bukatin, Steve Matthews
We consider dataflow architecture for two classes of computations which admit taking linear combinations of execution runs: probabilistic sampling and generalized animation. We imp…
Almost Continuous Transformations of Software and Higher-order Dataflow Programming
Michael Bukatin, Steve Matthews
We consider two classes of stream-based computations which admit taking linear combinations of execution runs: probabilistic sampling and generalized animation. The dataflow archit…