Hierarchical Density Order Embeddings
Table 1: Classification accuracy on hypernym relationship test set from WordNet.
['Method', 'Test Accuracy (%)']
We compare our results with vector order-embeddings (VOE) by Vendrov et al. Another important baseline is the transitive closure, which requires no learning and classifies if a held-out edge is a hypernym relationship by determining if it is in the union of the training edges. and word2gauss† is the best performance of our replication significantly; this result highlights the fact that our different approach for training Gaussian embeddings can be crucial to learning hierarchical representations.