Machine Learning for Hilbert Series
| Autor: | Edward Hirst |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | INSPIRE-HEP |
| DOI: | 10.48550/arxiv.2203.06073 |
| Popis: | 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. Comment: Prepared for the proceedings of the Nankai Symposium on Mathematical Dialogues, 2021; 9 pages, 3 figures |
| Databáze: | OpenAIRE |
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