[felippee]

Why would you want that? Conv net is not some magic. It's just a crude way to reduce dimensionality by loosing spatial location. For some things it works, for some it doesn't.

I think the shift in thinking should rather be: instead of trying to build the best possible associative memory to associate some A with some B, take the memory modules we have (perhaps not perfect) and try to build something bigger out of them. A dynamical model of the observed reality seems like a great thing to build out of such modules.

And this is what the PVM is. Currently made out of shallow, plain vanilla perceptrons, builds a structure which can be arbitrarily deep. Without any "magical" tricks such as dropout, relu, convolution, pooling etc.