I have not. I have read the paper though. I do want to try it and likely will at some point.

Next up after this project is that I want to test some metalearning ideas. I read some papers where the idea is that all weights are actually tinier neural networks, all with the same parameters where you train it to learn backpropagation (or whatever learning algorithm it converges to). The paper I read this from argued it also worked for forward-only but my intuition doesn't quite understand how. I want to follow up a bit on this line of research and check if there's been any new developments since I read them and try them out in my own code.