37 citations · 54 across the 3 of their papers we have counts for
7 papers
Machine Learning Algebraic Geometry for Physics
Jiakang Bao, Yang-Hui He, Elli Heyes +1
We review some recent applications of machine learning to algebraic geometry and physics. Since problems in algebraic geometry can typically be reformulated as mappings between ten…
Machine Learning for Hilbert Series
Edward Hirst
Hilbert series are a standard tool in algebraic geometry, and more recently are finding many uses in theoretical physics. This summary reviews work applying machine learning to dat…
Machine Learning Calabi-Yau Hypersurfaces
David S. Berman, Yang-Hui He, Edward Hirst
We revisit the classic database of weighted-P4s which admit Calabi-Yau 3-fold hypersurfaces equipped with a diverse set of tools from the machine-learning toolbox. Unsupervised tec…
Dessins d'Enfants, Seiberg-Witten Curves and Conformal Blocks
Jiakang Bao, Omar Foda, Yang-Hui He +4
We show how to map Grothendieck's dessins d'enfants to algebraic curves as Seiberg-Witten curves, then use the mirror map and the AGT map to obtain the corresponding 4d $\mathcal{N…
Quiver Mutations, Seiberg Duality and Machine Learning
Jiakang Bao, Sebastián Franco, Yang-Hui He +3
We initiate the study of applications of machine learning to Seiberg duality, focusing on the case of quiver gauge theories, a problem also of interest in mathematics in the contex…
Machine-Learning Dessins d'Enfants: Explorations via Modular and Seiberg-Witten Curves
Yang-Hui He, Edward Hirst, Toby Peterken
We apply machine-learning to the study of dessins d'enfants. Specifically, we investigate a class of dessins which reside at the intersection of the investigations of modular subgr…