As far I know, my lab is one of the few places mixing symbolic learning with Deep Learning. Do you or anyone else know other modern attempts (Reinforcement Learning?) with this approach?
It felt to me like they had found a way to restrict "symbolic" data to a very narrow domain where issues like hierarchical structure was totally absent, and vectorial representation was therefore quite straight forward, and I wanted to figure out an alternative. Instead of restricting the kinds of symbolic data involved, do the full spectrum. I had the symbolic vector idea in my head for about two years as an answer to the representation problem, but I hadn't seen what the right answer was to the other aspects, at least not clearly. But that paper motivated me to start thinking about it again, and this time I saw the answer. :)
But I would caution against saying this is a Vector Symbolic Architecture; the representations are, as far as I know, quite distinct.