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Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators

Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators

Haakon Noren
Sølve Eidnes
E. Celledoni
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Papers citing "Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators"

6 / 6 papers shown
Title
Symplectic Neural Networks Based on Dynamical Systems
Symplectic Neural Networks Based on Dynamical Systems
Benjamin K Tapley
39
1
0
19 Aug 2024
Pseudo-Hamiltonian neural networks for learning partial differential equations
Pseudo-Hamiltonian neural networks for learning partial differential equations
Sølve Eidnes
K. Lye
28
10
0
27 Apr 2023
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models
Bayesian Identification of Nonseparable Hamiltonian Systems Using Stochastic Dynamic Models
Harsh Sharma
Nicholas Galioto
Alex A. Gorodetsky
Boris Kramer
41
3
0
15 Sep 2022
Learning Hamiltonians of constrained mechanical systems
Learning Hamiltonians of constrained mechanical systems
E. Celledoni
A. Leone
Davide Murari
B. Owren
AI4CE
44
17
0
31 Jan 2022
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
265
2,309
0
18 Oct 2020
Symplectic Recurrent Neural Networks
Symplectic Recurrent Neural Networks
Zhengdao Chen
Jianyu Zhang
Martín Arjovsky
Léon Bottou
152
221
0
29 Sep 2019