22 citations · 53 across the 18 of their papers we have counts for
4 papers · 1 filter
Box Embeddings: An open-source library for representation learning using geometric structures
Tejas Chheda, Purujit Goyal, Trang Tran +4
A major factor contributing to the success of modern representation learning is the ease of performing various vector operations. Recently, objects with geometric structures (eg. d…
Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings
Shib Sankar Dasgupta, Michael Boratko, Siddhartha Mishra +4
Learning representations of words in a continuous space is perhaps the most fundamental task in NLP, however words interact in ways much richer than vector dot product similarity c…
Probabilistic Box Embeddings for Uncertain Knowledge Graph Reasoning
Xuelu Chen, Michael Boratko, Muhao Chen +3
Knowledge bases often consist of facts which are harvested from a variety of sources, many of which are noisy and some of which conflict, resulting in a level of uncertainty for ea…
Modeling Fine-Grained Entity Types with Box Embeddings
Yasumasa Onoe, Michael Boratko, Andrew McCallum +1
Neural entity typing models typically represent fine-grained entity types as vectors in a high-dimensional space, but such spaces are not well-suited to modeling these types' compl…