17 citations · 62 across the 9 of their papers we have counts for
9 papers
Machine Learning in Physics and Geometry
Yang-Hui He, Elli Heyes, Edward Hirst
We survey some recent applications of machine learning to problems in geometry and theoretical physics. Pure mathematical data has been compiled over the last few decades by the co…
Clustering Cluster Algebras with Clusters
Man-Wai Cheung, Pierre-Philippe Dechant, Yang-Hui He +3
Classification of cluster variables in cluster algebras (in particular, Grassmannian cluster algebras) is an important problem, which has direct application to computations of scat…
Machine Learning Class Numbers of Real Quadratic Fields
Malik Amir, Yang-Hui He, Kyu-Hwan Lee +2
We implement and interpret various supervised learning experiments involving real quadratic fields with class numbers 1, 2 and 3. We quantify the relative difficulties in separatin…
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…
Cluster Algebras: Network Science and Machine Learning
Pierre-Philippe Dechant, Yang-Hui He, Elli Heyes +1
Cluster algebras have recently become an important player in mathematics and physics. In this work, we investigate them through the lens of modern data science, specifically with t…
From the String Landscape to the Mathematical Landscape: a Machine-Learning Outlook
Yang-Hui He
We review the recent programme of using machine-learning to explore the landscape of mathematical problems. With this paradigm as a model for human intuition - complementary to and…
Calabi-Yau Metrics, Energy Functionals and Machine-Learning
Anthony Ashmore, Lucille Calmon, Yang-Hui He +1
We apply machine learning to the problem of finding numerical Calabi-Yau metrics. We extend previous work on learning approximate Ricci-flat metrics calculated using Donaldson's al…
Machine-Learning Arithmetic Curves
Yang-Hui He, Kyu-Hwan Lee, Thomas Oliver
We show that standard machine-learning algorithms may be trained to predict certain invariants of low genus arithmetic curves. Using datasets of size around one hundred thousand, w…
Machine-learning a virus assembly fitness landscape
Pierre-Philippe Dechant, Yang-Hui He
Realistic evolutionary fitness landscapes are notoriously difficult to construct. A recent cutting-edge model of virus assembly consists of a dodecahedral capsid with correspo…