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Machine Learning Lie Structures & Applications to Physics
v1v2 (latest)

Machine Learning Lie Structures & Applications to Physics

Physics Letters B (PLB), 2020
2 November 2020
Heng-Yu Chen
Yang-Hui He
Shailesh Lal
Suvajit Majumder
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Machine Learning Lie Structures & Applications to Physics"

15 / 15 papers shown
Deep Learning based discovery of Integrable Systems
Deep Learning based discovery of Integrable Systems
Shailesh Lal
Suvajit Majumder
E. Sobko
277
3
0
13 Mar 2025
A Triumvirate of AI Driven Theoretical Discovery
A Triumvirate of AI Driven Theoretical Discovery
Yang-Hui He
AI4CE
298
17
0
30 May 2024
Optimal Potential Shaping on SE(3) via Neural ODEs on Lie Groups
Optimal Potential Shaping on SE(3) via Neural ODEs on Lie Groups
Yannik P. Wotte
Federico Califano
Stefano Stramigioli
AI4CE
288
3
0
25 Jan 2024
Learning to be Simple
Learning to be Simple
Yang-Hui He
Vishnu Jejjala
Challenger Mishra
Max Sharnoff
174
0
0
08 Dec 2023
Accelerated Discovery of Machine-Learned Symmetries: Deriving the
  Exceptional Lie Groups G2, F4 and E6
Accelerated Discovery of Machine-Learned Symmetries: Deriving the Exceptional Lie Groups G2, F4 and E6Physics Letters B (Phys. Lett. B), 2023
Roy T. Forestano
Konstantin T. Matchev
Katia Matcheva
Alexander Roman
Eyup B. Unlu
Sarunas Verner
275
7
0
10 Jul 2023
Black holes and the loss landscape in machine learning
Black holes and the loss landscape in machine learningJournal of High Energy Physics (JHEP), 2023
P. Kumar
Taniya Mandal
Swapnamay Mondal
261
2
0
26 Jun 2023
Discovering Sparse Representations of Lie Groups with Machine Learning
Discovering Sparse Representations of Lie Groups with Machine LearningPhysics Letters B (Phys. Lett. B), 2023
Roy T. Forestano
Konstantin T. Matchev
Katia Matcheva
Alexander Roman
Eyup B. Unlu
Sarunas Verner
265
10
0
10 Feb 2023
Oracle-Preserving Latent Flows
Oracle-Preserving Latent Flows
Alexander Roman
Roy T. Forestano
Konstantin T. Matchev
Katia Matcheva
Eyup B. Unlu
DRL
313
6
0
02 Feb 2023
Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras
  from First Principles
Deep Learning Symmetries and Their Lie Groups, Algebras, and Subalgebras from First Principles
Roy T. Forestano
Konstantin T. Matchev
Katia Matcheva
Alexander Roman
Eyup B. Unlu
Sarunas Verner
AI4CE
304
26
0
13 Jan 2023
Machine learning of the well known things
Machine learning of the well known thingsTheoretical and mathematical physics (TMP), 2022
V. Dolotin
A. Morozov
A. Popolitov
OOD
149
3
0
25 Apr 2022
From the String Landscape to the Mathematical Landscape: a
  Machine-Learning Outlook
From the String Landscape to the Mathematical Landscape: a Machine-Learning Outlook
Yang-Hui He
331
5
0
12 Feb 2022
Machine learning a manifold
Machine learning a manifold
Sean Craven
Djuna Croon
Daniel J. Cutting
R. Houtz
217
11
0
14 Dec 2021
Machine-Learning Mathematical Structures
Machine-Learning Mathematical Structures
Yang-Hui He
263
45
0
15 Jan 2021
Neural Networks and Quantum Field Theory
Neural Networks and Quantum Field Theory
James Halverson
Anindita Maiti
Keegan Stoner
392
93
0
19 Aug 2020
Explore and Exploit with Heterotic Line Bundle Models
Explore and Exploit with Heterotic Line Bundle ModelsFortschritte der Physik (Fortschr. Phys.), 2020
Magdalena Larfors
Robin Schneider
307
40
0
10 Mar 2020
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