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arXiv · 2109.04997

Box Embeddings: An open-source library for representation learning using geometric structures

Tejas Chheda·Purujit Goyal·Trang Tran·Dhruvesh Patel·Michael Boratko·Shib Sankar Dasgupta·Andrew McCallum
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Abstract

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. distributions, complex or hyperbolic vectors, or regions such as cones, disks, or boxes) have been explored for their alternative inductive biases and additional representational capacities. In this work, we introduce Box Embeddings, a Python library that enables researchers to easily apply and extend probabilistic box embeddings.

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Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, Andrew McCallum. 2021-09-10. Box Embeddings: An open-source library for representation learning using geometric structures. https://arxiv.org/abs/2109.04997

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