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Data-driven modelling of brain activity using neural networks, Diffusion
  Maps, and the Koopman operator

Data-driven modelling of brain activity using neural networks, Diffusion Maps, and the Koopman operator

24 April 2023
I. Gallos
Daniel Lehmberg
Felix Dietrich
Constantinos Siettos
ArXiv (abs)PDFHTML

Papers citing "Data-driven modelling of brain activity using neural networks, Diffusion Maps, and the Koopman operator"

3 / 3 papers shown
Title
RandONet: Shallow-Networks with Random Projections for learning linear
  and nonlinear operators
RandONet: Shallow-Networks with Random Projections for learning linear and nonlinear operators
Gianluca Fabiani
Ioannis G. Kevrekidis
Constantinos Siettos
A. Yannacopoulos
104
13
0
08 Jun 2024
A physics-informed neural network method for the approximation of slow
  invariant manifolds for the general class of stiff systems of ODEs
A physics-informed neural network method for the approximation of slow invariant manifolds for the general class of stiff systems of ODEs
Dimitrios G. Patsatzis
Lucia Russo
Constantinos Siettos
PINN
67
3
0
18 Mar 2024
Early warning indicators via latent stochastic dynamical systems
Early warning indicators via latent stochastic dynamical systems
Lingyu Feng
Ting Gao
Wang Xiao
Jinqiao Duan
61
3
0
07 Sep 2023
1