# Notes on: Trouillon, Th\'eo, Welbl, J., Riedel, S., Gaussier, \'Eric, & Bouchard, G. (2016): Complex embeddings for simple link prediction

## Overview

- Relational models ought to be able to
- Learn:
- Reflexivity / irreflexivity
- Symmetry / antisymmetric
- Transistivity

- be linear in both time and memory to scale

- Standard embedding-approaches satisfy the above but has a problem:
*anti-symmetry* blows up the parameter space
- Attempts to solve the concern above using
*complex* embeddings, which can model anti-symmetry of relations