| Generative AI for brane configurations and coamoeba |
Mathematical Physics, VAE |
Physical Review D 2025 |
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| Hilbert series, machine learning, and applications to physics |
Algebraic Geometry, Mathematical Physics, Neural Network |
Physics Letters B 2024 |
Code |
| Machine learning BPS spectra and the gap conjecture |
Mathematical Physics, PCA |
Physical Review D 2024 |
|
| Machine learning Calabi-Yau hypersurfaces |
Mathematical Physics |
Physical Review D 2022 |
|
| Machine learning for complete intersection Calabi-Yau manifolds: a methodological study |
Mathematical Physics |
Physical Review D 2021 |
|
| Machine Learning in the String Landscape |
Mathematical Physics |
JHEP 2017 |
|
| Machine Learning Kreuzer–Skarke Calabi–Yau Threefolds |
Mathematical Physics, Algebraic Geometry, Neural Network |
arXiv 2025 |
|
| Machine learning of Calabi-Yau volumes |
Mathematical Physics, CNN, Linear Regression |
Physical Review D 2017 |
|
| Machine learning Sasakian G2 topology on contact Calabi-Yau 7-manifolds |
Mathematical Physics, Neural Network |
Physics Letters B 2024 |
Code |
| Machine-learning dessins d'enfants: explorations via modular and Seiberg–Witten curves |
Algebraic Geometry, Mathematical Physics |
Journal of Physics A 2021 |
|
| Neural network approximations for Calabi-Yau metrics |
Mathematical Physics, Neural Network |
JHEP 2022 |
|
| New Calabi–Yau manifolds from genetic algorithms |
Algebraic Geometry, Mathematical Physics, Genetic Algorithm |
Physics Letters B 2024 |
|
| Rigor with Machine Learning from Field Theory to the Poincaré Conjecture |
Geometry, Mathematical Physics |
Nature Reviews Physics 2024 |
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