Machine Learning for Hilbert Series

Edward Hirst ()
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Edward Hirst: University of London, Department of Mathematics, City

A chapter in Nankai Symposium on Mathematical Dialogues, 2026, pp 181-190 from Springer

Abstract: 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 Hilbert series to determine geometric properties of the underlying algebraic variety; and was prepared for the proceedings of the Nankai Symposium on Mathematical Dialogues, 2021.

Date: 2026
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-19-2328-9_21

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DOI: 10.1007/978-981-19-2328-9_21

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