mlsanityData to 14 Oct 2026

Deep learning complete intersection Calabi-Yau manifolds

arXiv 2311.11847 ↗First posted 20 Nov 2023hep-th cs.LG math.AGcited by 1

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Abstract (arXiv)

We review advancements in deep learning techniques for complete intersection Calabi-Yau (CICY) 3- and 4-folds, with the aim of understanding better how to handle algebraic topological data with machine learning. We first discuss methodological aspects and data analysis, before describing neural networks architectures. Then, we describe the state-of-the art accuracy in predicting Hodge numbers. We include new results on extrapolating predictions from low to high Hodge numbers, and conversely.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 22 of its 59 references that are in the map. First posted on arXiv 20 Nov 2023.

Builds on

22 of 59 references.

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10 more
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Citing papers per year: 2024: 1.

1 paper.

  1. 2024Deep Learning Calabi-Yau four folds with hybrid and recurrent neural network architecturescited by 2