Can any of the Julia machine learning frameworks do reservoir computing or echo state computing? Are there examples how to configure Flux.jl or Knet.jl to do either of these on a simple problem?
As far as I understand it, reservoir computing is a form of recurrent neural network in which the weights and connections of the network and the input->network map are randomly assigned and held fixed, and training is applied only to the network-> output map.
A student of mine wants to replicate and extend the results of the following paper, which applies reservoir computing to predicting chaotic and spatiotemporally chaotic dynamical systems. Neither of us knows much about machine learning; we’re hoping to learn though this project.
I’m going to start digging into the Knet tutorial…