Machine Learning for Hilbert Series
High Energy Physics - Theory
2022-03-14 v1 Algebraic Geometry
Abstract
Hilbert series are a standard tool in algebraic geometry, and more recently are finding many uses in theoretical physics. This summary reviews work applying machine learning to databases of them; and was prepared for the proceedings of the Nankai Symposium on Mathematical Dialogues, 2021.
Cite
@article{arxiv.2203.06073,
title = {Machine Learning for Hilbert Series},
author = {Edward Hirst},
journal= {arXiv preprint arXiv:2203.06073},
year = {2022}
}
Comments
Prepared for the proceedings of the Nankai Symposium on Mathematical Dialogues, 2021; 9 pages, 3 figures