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Items where Author is "Hirst, E."

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Number of items: 9.

Article

Chen, S., Dechant, P. P., He, Y. H. , Heyes, E., Hirst, E. & Riabchenko, D. ORCID: 0009-0005-8099-8628 (2024). Machine Learning Clifford invariants of ADE Coxeter elements. Advances in Applied Clifford Algebras, 34(3), article number 20. doi: 10.1007/s00006-024-01325-y

Arias-Tamargo, G., He, Y-H. ORCID: 0000-0002-0787-8380, Heyes, E. , Hirst, E. ORCID: 0000-0003-1699-4399 & Rodriguez-Gomez, D. (2022). Brain webs for brane webs. Physics Letters B, 833, article number 137376. doi: 10.1016/j.physletb.2022.137376

Bao, J. ORCID: 0000-0002-9583-1696, He, Y-H. ORCID: 0000-0002-0787-8380, Hirst, E. ORCID: 0000-0003-1699-4399 , Hofscheier, J., Kasprzyk, A. & Majumder, S. (2022). Hilbert Series, Machine Learning, and Applications to Physics. Physics Letters B, 827, article number 136966. doi: 10.1016/j.physletb.2022.136966

Bao, J. ORCID: 0000-0002-9583-1696, Hanany, A., He, Y-H. ORCID: 0000-0002-0787-8380 & Hirst, E. ORCID: 0000-0003-1699-4399 (2022). Some open questions in quiver gauge theory. Proyecciones, 41(2), pp. 355-386. doi: 10.22199/issn.0717-6279-5274

Berman, D. S., He, Y-H. ORCID: 0000-0002-0787-8380 & Hirst, E. ORCID: 0000-0003-1699-4399 (2022). Machine learning Calabi-Yau hypersurfaces. Physical Review D, 105(6), article number 066002. doi: 10.1103/physrevd.105.066002

Bao, J., He, Y-H., Hirst, E. ORCID: 0000-0003-1699-4399 & Pietromonaco, S. (2021). Lectures on the Calabi-Yau Landscape. Fields Institute Monographs, 2293, doi: 10.1007/978-3-030-77562-9

Bao, J. ORCID: 0000-0002-9583-1696, Foda, O., He, Y-H. ORCID: 0000-0002-0787-8380 , Hirst, E. ORCID: 0000-0003-1699-4399, Read, J., Xiao, Y. & Yagi, F. (2021). Dessins d'enfants, Seiberg-Witten curves and conformal blocks. Journal of High Energy Physics, 2021(5), article number 65. doi: 10.1007/jhep05(2021)065

Bao, J. ORCID: 0000-0002-9583-1696, Franco, S., He, Y-H. ORCID: 0000-0002-0787-8380 , Hirst, E. ORCID: 0000-0003-1699-4399, Musiker, G. & Xiao, Y. (2020). Quiver mutations, Seiberg duality, and machine learning. Physical Review D (PRD), 102(8), article number 086013. doi: 10.1103/physrevd.102.086013

Thesis

Hirst, E. (2023). Machine-Learning and Data Science Techniques in String and Gauge Theories. (Unpublished Doctoral thesis, City, University of London)

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