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We survey some recent applications of machine learning to problems in geometry and theoretical physics.
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“Uncovering the Symmetries on [p,q] 7-branes: Beyond the Kodaira Classification”
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Maximilian Kreuzer and Harald Skarke · 2000
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Igor. Klebanov and Matthew. Strassler · 2000
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“Scalar Curvature and Projective Embeddings, I”
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“Lectures on the Calabi-Yau Landscape”, 2020
Jiakang Bao, Yang-Hui He, Edward Hirst and Stephen Pietromonaco · 2001
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“Cluster Algebras I: Foundations”
Sergey Fomin and Andrei Zelevinsky · 2002
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“De Sitter vacua in string theory”
Shamit Kachru, Renata Kallosh, Andrei. Linde and Sandip. Trivedi · 2003
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“Duality walls, duality trees and fractional branes”, 2003
Sebastian Franco, Amihay Hanany, Yang-Hui He and Pavlos Kazakopoulos · 2003
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“Scalar curvature and projective embeddings, II”
S. Donaldson · 2004
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“Some numerical results in complex differential geometry”
S.. Donaldson · 2005
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“Numerical Calabi-Yau metrics”
Michael. Douglas, Robert. Karp, Sergio Lukic and Rene Reinbacher · 2008
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“Calabi-Yau Metrics for Quotients and Complete Intersections”
Volker Braun, Tamaz Brelidze, Michael. Douglas and Burt. Ovrut · 2008
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“Dimer models from mirror symmetry and quivering amoebae”
Bo Feng, Yang-Hui He, Kristian. Kennaway and Cumrun Vafa · 2008
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“Visualizing High-Dimensional Data Using t-SNE”
Laurens van Maaten and Geoffrey. Hinton · 2008
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“Quiver Mutations, Seiberg Duality and Machine Learning”
Jiakang Bao et al · 2020
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“Advancing mathematics by guiding human intuition with AI”
Alex Davies et al · 2021
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“Learning Size and Shape of Calabi-Yau Spaces”
Magdalena Larfors, Andre Lukas, Fabian Ruehle and Robin Schneider · 2021
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“The Calabi-Yau Landscape: From Geometry, to Physics, to Machine Learning”, Lecture Notes in Mathematics, 2021
Yang-Hui He · 2021
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“Machine-Learning Mathematical Structures”, 2021
Yang-Hui He · 2021
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“Canonical toric Fano threefolds”
Alexander Kasprzyk · 2010
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“Genetic Algorithms and the Search for Viable String Vacua”
Steven Abel and John Rizos · 2014
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“A Calabi-Yau Database: Threefolds Constructed from the Kreuzer-Skarke List”
Ross Altman et al · 2015
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“Deep-Learning the Landscape”, 2017
Yang-Hui He · 2017
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“Machine Learning in the String Landscape”
Jonathan Carifio, James Halverson, Dmitri Krioukov and Brent. Nelson · 2017
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“Machine Learning of Calabi-Yau Volumes”
Daniel Krefl and Rak-Kyeong Seong · 2017
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“Neural Networks and Quantum Field Theory”
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“Mathematica, Version 13.1” Champaign, IL, 2022
Wolfram, Inc · 2022
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“CYJAX: A package for Calabi-Yau metrics with JAX”, 2022
Mathis Gerdes and Sven Krippendorf · 2022
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“Machine Learning Algebraic Geometry for Physics”, 2022
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“Machine learning Calabi-Yau hypersurfaces”
David. Berman, Yang-Hui He and Edward Hirst · 2022
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“Neurons on Amoebae”
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“Mahler Measuring the Genetic Code of Amoebae”, 2022
Siqi Chen et al · 2022
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“Cluster Algebras: Network Science and Machine Learning”, 2022
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“Clustering Cluster Algebras with Clusters”, 2022
Man-Wai Cheung et al · 2022
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“Brain webs for brane webs”
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“The Inverse of Exact Renormalization Group Flows as Statistical Inference”, 2022
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