(A writeup of a side project that I’m working on. I’ve posted working code on Github for both pytorch and tensorflow.) Imagine a deep neural network that has many chances to query information from its input, rather than just one chance, a network that reacts to the currently accumulated information to select its next query. How might this network work differently from today’s neural networks? I think this type of deep network would be more opportunistic and symbiotic with the input. Rat...
