no code implementations • 28 Sep 2020 • Chase John Gaudet, Anthony S. Maida
It has been shown that the core reasons that complex and hypercomplex valued neural networks offer improvements over their real-valued counterparts is the fact that aspects of their algebra forces treating multi-dimensional data as a single entity (forced local relationship encoding) with an added benefit of reducing parameter count via weight sharing.
