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Machine Learning Algebraic Geometry for Physics
We review some recent applications of machine learning to algebraic geometry and physics.
Neurons on Amoebae
We apply methods of machine-learning, such as neural networks, manifold learning and image processing, in order to study 2-dimensional amoebae in algebraic geometry and string theory.
Chiral Rings, Futaki Invariants, Plethystics, and Groebner Bases
We study chiral rings of 4d $\mathcal{N}=1$ supersymmetric gauge theories via the notion of K-stability.
High Energy Physics - Theory Algebraic Geometry
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