FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities

1 October 2022

Papers citing "FINDE: Neural Differential Equations for Finding and Preserving Invariant Quantities"

7 / 7 papers shown

Title
Learning Dynamical Systems from Noisy Data with Inverse-Explicit Integrators Haakon Noren Sølve Eidnes E. Celledoni 23 3 0 06 Jun 2023
Learning Hamiltonians of constrained mechanical systems E. Celledoni A. Leone Davide Murari B. Owren AI4CE 44 17 0 31 Jan 2022
Noether Networks: Meta-Learning Useful Conserved Quantities Ferran Alet Dylan D. Doblar Allan Zhou J. Tenenbaum Kenji Kawaguchi Chelsea Finn 75 26 0 06 Dec 2021
Automatic Symmetry Discovery with Lie Algebra Convolutional Network Nima Dehmamy Robin Walters Yanchen Liu Dashun Wang Rose Yu AI4CE 78 81 0 15 Sep 2021
A Practical Method for Constructing Equivariant Multilayer Perceptrons for Arbitrary Matrix Groups Marc Finzi Max Welling A. Wilson 79 186 0 19 Apr 2021
Lagrangian Neural Networks M. Cranmer S. Greydanus Stephan Hoyer Peter W. Battaglia D. Spergel S. Ho PINN 139 425 0 10 Mar 2020
Symplectic Recurrent Neural Networks Zhengdao Chen Jianyu Zhang Martín Arjovsky Léon Bottou 152 220 0 29 Sep 2019