Reviews: Poincaré Embeddings for Learning Hierarchical Representations

Summary The paper proposes a link prediction model that embeds symbols in a hyperbolic space using Poincaré embeddings. In this space, tree structures can more easily be represented as the distance to points increases exponentially w.r.t. The paper is motivated and written well. Furthermore, the presented method is intriguing and I believe it will have a notable impact on link prediction research. My concerns are regarding the comparison to state-of-the-art link prediction and how the method performs if the assumption about a hierarchy in the data is dropped.