# Discrete neural nets and polymorphic learning

arXiv: https://arxiv.org/abs/2308.00677 · HTML: https://mlsanity.com/paper/2308.00677/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 9 references that are in the map.
- First posted on arXiv 29 Jul 2023.

## Builds on (most cited first, 1 of 1)

- [What is an equivariant neural network?](https://mlsanity.com/paper/2205.07362/) (2022)

## Abstract (arXiv)

Theorems from universal algebra such as that of Murskiui from the 1970s have a striking similarity to universal approximation results for neural nets along the lines of Cybenko's from the 1980s. We consider here a discrete analogue of the classical notion of a neural net which places these results in a unified setting. We introduce a learning algorithm based on polymorphisms of relational structures and show how to use it for a classical learning task.