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Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"

Home Page: https://ngorbach.github.io/Variational_Gradient_Matching_for_Dynamical_Systems/#17

Jupyter Notebook 86.39% Python 0.41% MATLAB 0.25% HTML 11.93% TeX 1.03%
dynamical-systems dynamical-modeling inference mean-field-theory scalable lotka-volterra lorenz-attractor nips-paper variational-inference identification

variational_gradient_matching_for_dynamical_systems's Introduction

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Variational Gradient Matching for Dynamical Systems

code documentation | NIPS 2017 conference publication | arXiv version | doctoral thesis | supplementary paper


Contents

Sample code for the NIPS (2018) paper Scalable Variational Inference for Dynamical Systems by Nico S. Gorbach, Stefan Bauer and Joachim M. Buhmann. Please cite our paper if you use our program for a further publication. The derivations of the formulas used in this code are also given in this doctoral thesis as well as in parts of Wenk et al. (2018).

Run the Python scripts VGM_for_Lotka_Volterra.py or VGM_for_Lorenz_attractor.py. Alternatively, you can also run the Jupyter Notebook scripts VGM_for_Lotka_Volterra.ipynb or VGM_for_Lorenz_attractor.ipynb.


Some Results

Lotka-Volterra

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Lorenz 96

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Lorenz Attractor

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Dynamic Causal Modeling

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Authors

Nico Stephan Gorbach and Stefan Bauer, email: [email protected]

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variational_gradient_matching_for_dynamical_systems's Issues

Can't run VGM_for_Lorenz_attractor.py

Traceback (most recent call last):
  File "/home/joao/github/Variational_Gradient_Matching_for_Dynamical_Systems/VGM_for_Lorenz_attractor.py", line 125, in <module>
    state_couplings = find_state_couplings_in_odes(odes,symbols)
  File "./VGM_modules/import_odes.py", line 82, in find_state_couplings_in_odes
    membership = ismember(symbols.state,odes_sym[u].free_symbols)
AttributeError: 'function' object has no attribute 'free_symbols'

Would suggest adding a requirements.txt to the repo.

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