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Learning stochastic dynamical systems with neural networks mimicking the
  Euler-Maruyama scheme

Learning stochastic dynamical systems with neural networks mimicking the Euler-Maruyama scheme

18 May 2021
Noura Dridi
Lucas Drumetz
Ronan Fablet
ArXivPDFHTML

Papers citing "Learning stochastic dynamical systems with neural networks mimicking the Euler-Maruyama scheme"

2 / 2 papers shown
Title
One-Shot Learning of Stochastic Differential Equations with Data Adapted
  Kernels
One-Shot Learning of Stochastic Differential Equations with Data Adapted Kernels
Matthieu Darcy
B. Hamzi
Giulia Livieri
H. Owhadi
P. Tavallali
36
26
0
24 Sep 2022
An end-to-end deep learning approach for extracting stochastic dynamical
  systems with $α$-stable Lévy noise
An end-to-end deep learning approach for extracting stochastic dynamical systems with ααα-stable Lévy noise
Cheng Fang
Yubin Lu
Ting Gao
Jinqiao Duan
55
16
0
31 Jan 2022
1