Poincaré Embeddings
Poincaré Embeddings
**Poincaré Embeddings** learn hierarchical representations of symbolic data by embedding them into hyperbolic space -- or more precisely into an $n$-dimensional Poincaré ball. Due to the underlying hyperbolic geometry, this allows for learning of parsimonious representations of symbolic data by simultaneously capturing hierarchy and similarity. Embeddings are learnt based on
Riemannian optimization.
Poincaré Embeddings for Learning Hierarchical Representations
https://paperswithcode.com/paper/poincare-embeddings-for-learning-hierarchical
Poincaré Embeddings for Learning Hierarchical Representations