ngorbach / Variational_gradient_matching_for_dynamical_systems
Sample code for the NIPS paper "Scalable Variational Inference for Dynamical Systems"
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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
Lorenz 96
Lorenz Attractor
Dynamic Causal Modeling
Authors
Nico Stephan Gorbach and Stefan Bauer, email: [email protected]
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