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Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe

Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe

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Papers citing "Machine learning and serving of discrete field theories -- when artificial intelligence meets the discrete universe"

7 / 7 papers shown
Title
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery
Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery
Yana Lishkova
P. Scherer
Steffen Ridderbusch
M. Jamnik
Pietro Lio
Sina Ober-Blobaum
Christian Offen
PINN
73
7
0
28 Jan 2025
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks
Approximation of nearly-periodic symplectic maps via structure-preserving neural networks
Valentin Duruisseaux
J. Burby
Q. Tang
33
11
0
11 Oct 2022
Lagrangian Density Space-Time Deep Neural Network Topology
Lagrangian Density Space-Time Deep Neural Network Topology
B. Bishnoi
PINN
22
1
0
30 Jun 2022
Machine Learning for Discovering Effective Interaction Kernels between Celestial Bodies from Ephemerides
Machine Learning for Discovering Effective Interaction Kernels between Celestial Bodies from Ephemerides
Ming Zhong
Jason D Miller
Mauro Maggioni
16
1
0
26 Aug 2021
Lagrangian Neural Networks
Lagrangian Neural Networks
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
PINN
139
424
0
10 Mar 2020
Symplectic Recurrent Neural Networks
Symplectic Recurrent Neural Networks
Zhengdao Chen
Jianyu Zhang
Martín Arjovsky
Léon Bottou
152
220
0
29 Sep 2019
Learning Symbolic Physics with Graph Networks
Learning Symbolic Physics with Graph Networks
M. Cranmer
Rui Xu
Peter W. Battaglia
S. Ho
PINN
AI4CE
188
84
0
12 Sep 2019