262 citations · 474 across the 7 of their papers we have counts for
7 papers
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 matrix machines as programmable, dynamically expandable, self-referential generalized recurrent neural networks
Michael Bukatin, Steve Matthews, Andrey Radul
Dataflow matrix machines are a powerful generalization of recurrent neural networks. They work with multiple types of linear streams and multiple types of neurons, including higher…
Dataflow Matrix Machines as a Generalization of Recurrent Neural Networks
Michael Bukatin, Steve Matthews, Andrey Radul
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,…
Representation theory of the vertex algebra
Victor Kac, Andrey Radul
In our paper~\cite{KR} we began a systematic study of representations of the universal central extension $\widehat{\Cal D}\/$ of the Lie algebra of differential operators on the ci…
W_{1+\infty} and W(gl_N) with central charge N
E. Frenkel, V. Kac, A. Radul +1
We study representations of the central extension of the Lie algebra of differential operators on the circle, the W-infinity algebra. We obtain complete and specialized character f…