Machine-Learning and Data Science Techniques in String and Gauge Theories
Lead Research Organisation:
City, University of London
Department Name: Sch of Engineering and Mathematical Sci
Abstract
Machine-Learning and Data Science Techniques in String and Gauge Theories
Organisations
People |
ORCID iD |
| Yang-Hui He (Primary Supervisor) | |
| Edward Hirst (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| ST/S505341/1 | 01/10/2019 | 30/09/2023 | |||
| 2283750 | Studentship | ST/S505341/1 | 01/10/2019 | 30/03/2023 | Edward Hirst |
| Description | Data Science and Machine-Learning techniques have been tested ona variety of mathematical objects used in various subfields of geometry and theoretical physics. The successes of certain techniques have been documented, identifying a new computational avenue for research beyond techniques currently used. |
| Exploitation Route | More advanced techniques would hope to help identify new phenomena and hence uncover further interconnections within the mathematics that can aid interpretation and stimulate further research. |
| Sectors | Other |