Awesome AI for Math

A curated list of awesome papers on AI for Mathematics.

View the Project on GitHub seewoo5/awesome-ai-for-math

Mathematical Physics papers

Title Subject(s) Venue & Year Links & Resources
Generative AI for brane configurations and coamoeba Mathematical Physics, VAE Physical Review D 2025
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 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