# Information-Geometric Set Embeddings (IGSE): From Sets to Probability Distributions

arXiv: https://arxiv.org/abs/1911.12463 · HTML: https://mlsanity.com/paper/1911.12463/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Nov 2019.

## Built on by (most cited first, 3 of 3)

- [Logic Embeddings for Complex Query Answering](https://mlsanity.com/paper/2103.00418/) (2021)
- [Neural Program Synthesis with Query](https://mlsanity.com/paper/2205.07857/) (2022)
- [Online Symbolic Regression with Informative Query](https://mlsanity.com/paper/2302.10539/) (2023)

## Abstract (arXiv)

This letter introduces an abstract learning problem called the "set embedding": The objective is to map sets into probability distributions so as to lose less information. We relate set union and intersection operations with corresponding interpolations of probability distributions. We also demonstrate a preliminary solution with experimental results on toy set embedding examples.