mlsanityData to 14 Oct 2026

Machine Learning Kreuzer--Skarke Calabi--Yau Threefolds

arXiv 2112.09117 ↗First posted 16 Dec 2021hep-th cs.LG math.AGcited by 8

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Abstract (arXiv)

Using a fully connected feedforward neural network we study topological invariants of a class of Calabi--Yau manifolds constructed as hypersurfaces in toric varieties associated with reflexive polytopes from the Kreuzer--Skarke database. In particular, we find the existence of a simple expression for the Euler number that can be learned in terms of limited data extracted from the polytope and its dual.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 13 of its 62 references that are in the map. First posted on arXiv 16 Dec 2021.

Builds on

13 of 62 references.

References · 13

  1. 2014Adam: A Method for Stochastic Optimizationcited by 37,240
  2. 2018Fashionable Modelling with Fluxcited by 53
  3. 2020Learning to Unknotcited by 40
  4. 2020Neural Network Approximations for Calabi-Yau Metricscited by 32
  5. 2021Learning Size and Shape of Calabi-Yau Spacescited by 28
  6. 2019Machine learning Calabi-Yau metricscited by 23
  7. 2018Machine Learning CICY Threefoldscited by 22
  8. 2020Machine learning for complete intersection Calabi-Yau manifolds: a methodological studycited by 17
  9. 2020Machine Learning Calabi-Yau Four-foldscited by 17
  10. 2020Inception Neural Network for Complete Intersection Calabi-Yau 3-foldscited by 14
  11. 2020Disentangling a Deep Learned Volume Formulacited by 12
  12. 2021Learning knot invariants across dimensionscited by 12
1 more
  1. 2020Explore and Exploit with Heterotic Line Bundle Modelscited by 11

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Cited by year

Citing papers per year: 2022: 3; 2023: 4; 2024: 1.

8 papers.

  1. 2022Cluster Algebras: Network Science and Machine Learningcited by 9
  2. 2023Machine Learning Clifford invariants of ADE Coxeter elementscited by 6
  3. 2024A Triumvirate of AI Driven Theoretical Discoverycited by 5
  4. 2023Machine learning assisted exploration for affine Deligne-Lusztig varietiescited by 3
  5. 2022From the String Landscape to the Mathematical Landscape: a Machine-Learning Outlookcited by 2
  6. 2022Identifying equivalent Calabi--Yau topologies: A discrete challenge from math and physics for machine learningcited by 2
  7. 2023Neural Polytopescited by 1
  8. 2023Calabi-Yau Four/Five/Six-folds as mathbbPnw Hypersurfaces: Machine Learning, Approximation, and Generationcited by 0