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

- Institution: CERN
- Department: TH institutes
- Speaker: Yang-Hui He
- Year: 2019
- Language: English
- Subjects: Mathematics
- Source: [CERN](https://videos.cern.ch/record/3007150)
- Licence: [CERN](http://copyright.web.cern.ch)
- Who can watch: Tweens profiles and older (sources give no ratings; placed by Invisible Network from the source's own words)

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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## Lectures

1. [Machine-Learning Algebraic & Geometric Structures: Implications to String Pheno](https://invisiblenetwork.ai/learn/cern/3007150/08aa6d7b0d93), 48 min (CERN's player)