PINNs approximate near-minimal surfaces bounding knots in S^3; their self-intersection numbers align with Fine's conjecture predictions derived from the HOMFLY polynomial.
Learning Size and Shape of Calabi– Yau Spaces
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
Global invariant neural models for Kähler potentials outperform local baselines on geometric diagnostics for hard Calabi-Yau hypersurfaces.
Approximate analytic Ricci-flat metrics on a one-parameter bi-cubic Calabi-Yau family with explicit moduli dependence obtained via symbolic regression on numerical data, achieving percent-level agreement.
Explicit 11D solutions show flux stabilization of T^4/Z2 moduli in EFT does not match the full theory, with non-Lorentz-invariant deformations stabilizing a mix of volume and shape moduli instead.
citing papers explorer
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Minimal surfaces, Knots, and Neural Networks
PINNs approximate near-minimal surfaces bounding knots in S^3; their self-intersection numbers align with Fine's conjecture predictions derived from the HOMFLY polynomial.
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GlobalCY I: A JAX Framework for Globally Defined and Symmetry-Aware Neural K\"ahler Potentials
Global invariant neural models for Kähler potentials outperform local baselines on geometric diagnostics for hard Calabi-Yau hypersurfaces.
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Calabi-Yau Metrics with Full Moduli Dependence
Approximate analytic Ricci-flat metrics on a one-parameter bi-cubic Calabi-Yau family with explicit moduli dependence obtained via symbolic regression on numerical data, achieving percent-level agreement.
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Lost in Translation: Moduli Stabilization from EFT to Eleven Dimensions
Explicit 11D solutions show flux stabilization of T^4/Z2 moduli in EFT does not match the full theory, with non-Lorentz-invariant deformations stabilizing a mix of volume and shape moduli instead.