Vector Symbolic Algebras and Neural Computation

Vector Symbolic Algebras (VSAs) are a family of frameworks developed to unify symbolic reasoning and connectionist models. In this way, they provide a rigorous way to talk about neural computation. While VSAs may appear a niche interest at first blush, they have ties to other well-established models of computation.

In this talk, Dr. Michael Furlong will highlight the connections between different computing models and underscore some of the computational benefits that can be gained by adopting VSAs as a computing model.