Anatomy of a Model

This module includes neural graph embedding models and support functions.

Knowledge graph embedding models are neural architectures that encode concepts from a knowledge graph (i.e., entities \(\mathcal{E}\) and relation types \(\mathcal{R}\)) into low-dimensional, continuous vectors \(\in \mathcal{R}^k\). Such knowledge graph embeddings have applications in knowledge graph completion, entity resolution, and link-based clustering, just to cite a few [NMTG16].