# Learning proofs for the classification of nilpotent semigroups

arXiv: https://arxiv.org/abs/2106.03015 · HTML: https://mlsanity.com/paper/2106.03015/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 26 references that are in the map.
- First posted on arXiv 6 Jun 2021.

## Builds on (most cited first, 7 of 7)

- [Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm](https://mlsanity.com/paper/1712.01815/) (2017)
- [A Convolutional Neural Network for Modelling Sentences](https://mlsanity.com/paper/1404.2188/) (2014)
- [Constructions in combinatorics via neural networks](https://mlsanity.com/paper/2104.14516/) (2021)
- [Deep-Learning the Landscape](https://mlsanity.com/paper/1706.02714/) (2017)
- [Learning selection strategies in Buchberger's algorithm](https://mlsanity.com/paper/2005.01917/) (2020)
- [Deep Learning Gauss-Manin Connections](https://mlsanity.com/paper/2007.13786/) (2020)
- [A Neural Network for Semigroups](https://mlsanity.com/paper/2103.07388/) (2021)

## Built on by (most cited first, 1 of 1)

- [Is deep learning a useful tool for the pure mathematician?](https://mlsanity.com/paper/2304.12602/) (2023)

## Abstract (arXiv)

Machine learning is applied to find proofs, with smaller or smallest numbers of nodes, for the classification of 4-nilpotent semigroups.