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Data-driven discovery of non-Newtonian astronomy via learning
  non-Euclidean Hamiltonian

Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian

30 September 2022
Oswin So
Gongjie Li
Evangelos A. Theodorou
Molei Tao
    AI4CE
ArXivPDFHTML

Papers citing "Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian"

6 / 6 papers shown
Title
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics
  Learning and Control
Port-Hamiltonian Neural ODE Networks on Lie Groups For Robot Dynamics Learning and Control
T. Duong
Abdullah Altawaitan
Jason Stanley
Nikolay A. Atanasov
25
10
0
17 Jan 2024
Hamiltonian Neural Networks with Automatic Symmetry Detection
Hamiltonian Neural Networks with Automatic Symmetry Detection
Eva Dierkes
Christian Offen
Sina Ober-Blobaum
K. Flaßkamp
17
7
0
19 Jan 2023
ModLaNets: Learning Generalisable Dynamics via Modularity and Physical
  Inductive Bias
ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias
Yupu Lu
Shi-Min Lin
Guanqi Chen
Jia-Yu Pan
32
7
0
24 Jun 2022
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable
  Contact Models
Extending Lagrangian and Hamiltonian Neural Networks with Differentiable Contact Models
Yaofeng Desmond Zhong
Biswadip Dey
Amit Chakraborty
52
34
0
12 Feb 2021
Lagrangian Neural Networks
Lagrangian Neural Networks
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
PINN
130
422
0
10 Mar 2020
Symplectic Recurrent Neural Networks
Symplectic Recurrent Neural Networks
Zhengdao Chen
Jianyu Zhang
Martín Arjovsky
Léon Bottou
146
219
0
29 Sep 2019
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