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Talk48 min

Machine-Learning Algebraic & Geometric Structures: Implications to String Pheno

Yang-Hui He · CERN

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About

We report some recent experiments in machine-learning applied to various mathematical problems such as computing Hodge numbers, recognizing elliptic fibrations, distinguishing finite simple groups, etc., many of which have direct consequences in string phenomenology. The mysterious success of the ML, often bypassing traditional expensive algorithms, potentially suggests hithertofore unseen structures..

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The talk

  1. Machine-Learning Algebraic & Geometric Structures: Implications to String Pheno 2019-06-21 · 48 min · CERN's player

Credits and licence

Institution
CERN
Department
TH institutes
Speaker
Yang-Hui He
Year
2019
Language
English
Subjects
Mathematics
Source
CERN
Licence
CERN, as CERN states it. CERN's terms
Attribution
© CERN. CERN provides its audiovisual media free of charge for educational and informational use, credited to CERN; this lecture is shown in CERN's own player.
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