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Machine Learning Lie Structures & Applications to Physics

Machine Learning Lie Structures & Applications to Physics

2 November 2020
Heng-Yu Chen
Yang-Hui He
Shailesh Lal
Suvajit Majumder
    AI4CE
ArXivPDFHTML

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

7 / 7 papers shown
Title
A Triumvirate of AI Driven Theoretical Discovery
A Triumvirate of AI Driven Theoretical Discovery
Yang-Hui He
AI4CE
45
4
0
30 May 2024
Discovering Sparse Representations of Lie Groups with Machine Learning
Discovering Sparse Representations of Lie Groups with Machine Learning
Roy T. Forestano
Konstantin T. Matchev
Katia Matcheva
Alexander Roman
Eyup B. Unlu
Sarunas Verner
35
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
24
5
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
28
21
0
13 Jan 2023
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
20
5
0
12 Feb 2022
Baryons from Mesons: A Machine Learning Perspective
Baryons from Mesons: A Machine Learning Perspective
Y. Gal
Vishnu Jejjala
D. M. Peña
Challenger Mishra
AI4CE
30
10
0
23 Mar 2020
Explore and Exploit with Heterotic Line Bundle Models
Explore and Exploit with Heterotic Line Bundle Models
Magdalena Larfors
Robin Schneider
34
38
0
10 Mar 2020
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