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Learning the parameters of a differential equation from its trajectory
  via the adjoint equation

Learning the parameters of a differential equation from its trajectory via the adjoint equation

17 June 2022
I. Fekete
A. Molnár
P. Simon
ArXivPDFHTML

Papers citing "Learning the parameters of a differential equation from its trajectory via the adjoint equation"

5 / 5 papers shown
Title
Augmented Neural ODEs
Augmented Neural ODEs
Emilien Dupont
Arnaud Doucet
Yee Whye Teh
BDL
127
626
0
02 Apr 2019
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
356
5,081
0
19 Jun 2018
Deep Neural Networks Motivated by Partial Differential Equations
Deep Neural Networks Motivated by Partial Differential Equations
Lars Ruthotto
E. Haber
AI4CE
102
488
0
12 Apr 2018
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and
  Numerical Differential Equations
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
Yiping Lu
Aoxiao Zhong
Quanzheng Li
Bin Dong
193
501
0
27 Oct 2017
Stable Architectures for Deep Neural Networks
Stable Architectures for Deep Neural Networks
E. Haber
Lars Ruthotto
128
727
0
09 May 2017
1