Publications: Dr Edward Hirst
Berglund P, Butbaia G, He Y-H, Heyes E, Hirst E, Jejjala V
(
2024
)
.
Generating Triangulations and Fibrations with Reinforcement Learning
.
Physics Letters B
Hirst E
(
2024
)
.
Calabi–Yau links and machine learning
.
International Journal of Data Science in the Mathematical Sciences
vol.
02
,
(
01
)
3
-
14
.
Hirst E, Schettini Gherardini T
(
2024
)
.
Calabi-Yau Four/Five/Six-folds as $\mathbb{P}_\textbf{w}^n$ Hypersurfaces: Machine Learning, Approximation, and Generation
.
Phys. Rev. D
vol.
109
,
106006
-
106006
.
Chen S, Dechant P-P, He Y-H, Heyes E, Hirst E, Riabchenko D
(
2024
)
.
Machine Learning Clifford Invariants of ADE Coxeter Elements
.
Advances in Applied Clifford Algebras
vol.
34
,
(
3
)
Aggarwal D, He Y-H, Heyes E, Hirst E, Earp HNS, Silva TSR
(
2024
)
.
Machine learning Sasakian and G2 topology on contact Calabi-Yau 7-manifolds
.
Physics Letters B
vol.
850
,
Berglund P, He Y-H, Heyes E, Hirst E, Jejjala V, Lukas A
(
2024
)
.
New Calabi–Yau manifolds from genetic algorithms
.
Physics Letters B
vol.
850
,
Bao J, He Y-H, Hirst E, Hofscheier J, Kasprzyk A, Majumder S
(
2024
)
.
Polytopes and machine learning
.
International Journal of Data Science in the Mathematical Sciences
vol.
01
,
(
02
)
181
-
211
.
Dechant P-P, He Y-H, Heyes E, Hirst E
(
2023
)
.
Cluster algebras: Network science and machine learning
.
Journal of Computational Algebra
vol.
8
,
Bao J, He Y-H, Hirst E
(
2023
)
.
Neurons on amoebae
.
Journal of Symbolic Computation
vol.
116
,
1
-
38
.
Cheung M-W, Dechant P-P, He Y-H, Heyes E, Hirst E, Li J-R
(
2023
)
.
Clustering cluster algebras with clusters
.
Advances in Theoretical and Mathematical Physics
vol.
27
,
(
3
)
797
-
828
.
He Y-H, Heyes E, Hirst E
(
2023
)
.
Machine learning in physics and geometry
.
Artificial Intelligence
,
vol.
49
,
Elsevier
Chen S, He Y-H, Hirst E, Nestor A, Zahabi A
(
2023
)
.
Mahler measuring the genetic code of amoebae
.
Advances in Theoretical and Mathematical Physics
vol.
27
,
(
5
)
1405
-
1461
.
Arias-Tamargo G, He Y-H, Heyes E, Hirst E, Rodriguez-Gomez D
(
2022
)
.
Brain webs for brane webs
.
Physics Letters B
vol.
833
,
Bao J, He Y-H, Hirst E, Hofscheier J, Kasprzyk A, Majumder S
(
2022
)
.
Hilbert series, machine learning, and applications to physics
.
Physics Letters B
vol.
827
,
Bao J, Hanany A, He Y-H, Hirst E
(
2022
)
.
Some open questions in quiver gauge theory
.
Proyecciones (Antofagasta)
vol.
41
,
(
2
)
355
-
386
.
Berman DS, He Y-H, Hirst E
(
2022
)
.
Machine learning Calabi-Yau hypersurfaces
.
Physical Review D
vol.
105
,
(
6
)
066002
-
066002
.
Bao J, Foda O, He Y-H, Hirst E, Read J, Xiao Y, Yagi F
(
2021
)
.
Dessins d’enfants, Seiberg-Witten curves and conformal blocks
.
Journal of High Energy Physics
vol.
2021
,
(
5
)
He Y-H, Hirst E, Peterken T
(
2021
)
.
Machine-learning dessins d’enfants: explorations via modular and Seiberg–Witten curves
.
Journal of Physics A: Mathematical and Theoretical
vol.
54
,
(
7
)
Bao J, Franco S, He Y-H, Hirst E, Musiker G, Xiao Y
(
2020
)
.
Quiver mutations, Seiberg duality, and machine learning
.
Physical Review D
vol.
102
,
(
8
)