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Found 8 papers, 5 papers with code
Learning 3-Manifold Triangulations
Real 3-manifold triangulations can be uniquely represented by isomorphism signatures.
Calabi-Yau Four/Five/Six-folds as $\mathbb{P}^n_\textbf{w}$ Hypersurfaces: Machine Learning, Approximation, and Generation
Using the knowledge of this classification, and the properties of the presented approximation, a novel dataset of transverse weight systems consisting of 7 weights was generated for a sum of weights $\leq 200$; producing a new database of Calabi-Yau five-folds, with their respective topological properties computed.
Machine Learning Clifford invariants of ADE Coxeter elements
This provides the perfect setup for machine learning, and indeed we see that the datasets can be machine learned to very high accuracy.
Machine Learning Algebraic Geometry for Physics
We review some recent applications of machine learning to algebraic geometry and physics.
Cluster Algebras: Network Science and Machine Learning
Network analysis methods are applied to the exchange graphs for cluster algebras of varying mutation types.
Machine Learning Calabi-Yau Hypersurfaces
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.
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.
Machine-Learning Dessins d'Enfants: Explorations via Modular and Seiberg-Witten Curves
We apply machine-learning to the study of dessins d'enfants.
