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Damped Cubic oscillator --- 0% noise.ipynb
Damped Cubic oscillator --- 0% noise.ipynb
 
 
Damped Cubic oscillator --- 1% noise.ipynb
Damped Cubic oscillator --- 1% noise.ipynb
 
 
Damped Cubic oscillator --- 10% noise --- variable timesteps.ipynb
Damped Cubic oscillator --- 10% noise --- variable timesteps.ipynb
 
 
Damped Cubic oscillator --- 10% noise.ipynb
Damped Cubic oscillator --- 10% noise.ipynb
 
 
Damped Cubic oscillator --- 25% noise.ipynb
Damped Cubic oscillator --- 25% noise.ipynb
 
 
Damped Cubic oscillator --- 5% noise.ipynb
Damped Cubic oscillator --- 5% noise.ipynb
 
 
Double Pendulum --- 0% Noise.ipynb
Double Pendulum --- 0% Noise.ipynb
 
 
Double Pendulum --- 1% Noise.ipynb
Double Pendulum --- 1% Noise.ipynb
 
 
Double Pendulum --- 10% Noise.ipynb
Double Pendulum --- 10% Noise.ipynb
 
 
Double Pendulum --- 5% Noise.ipynb
Double Pendulum --- 5% Noise.ipynb
 
 
Lorenz - Multi run - 5 % noise.ipynb
Lorenz - Multi run - 5 % noise.ipynb
 
 
Lorenz --- 0% noise.ipynb
Lorenz --- 0% noise.ipynb
 
 
Lorenz --- 1% Noise.ipynb
Lorenz --- 1% Noise.ipynb
 
 
Lorenz --- 10% Noise.ipynb
Lorenz --- 10% Noise.ipynb
 
 
Lorenz --- 15% Noise.ipynb
Lorenz --- 15% Noise.ipynb
 
 
Lorenz --- 5% Noise.ipynb
Lorenz --- 5% Noise.ipynb
 
 
Lorenz --- 5% noise --- Long time series.ipynb
Lorenz --- 5% noise --- Long time series.ipynb
 
 
Navier Stokes ODE --- 0% noise.ipynb
Navier Stokes ODE --- 0% noise.ipynb
 
 
Navier Stokes ODE --- 1% Noise.ipynb
Navier Stokes ODE --- 1% Noise.ipynb
 
 
PODcoefficients_run1.mat
PODcoefficients_run1.mat
 
 
README.md
README.md
 
 
pendulum_data.dat
pendulum_data.dat
 
 
utils.py
utils.py
 
 
utils_var_step.py
utils_var_step.py
 
 

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RKNN

Code used in `Deep learning of dynamics and signal noise decomposition with time-stepping constraints.'

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