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Model Learning

Matlab (R) library for model learning and model reduction. The main methods and algorithms implemented in the library have been introduced in the papers [1,2], wherein they are derived and documented.

For information about the installation and usage of the library, check out the documentation.

References

[1] F. Regazzoni, L. Dede', A. Quarteroni Machine learning for fast and reliable solution of time-dependent differential equations, Journal of Computational Physics (2019).

[2] F. Regazzoni, D. Chapelle, P. Moireau Combining Data Assimilation and Machine Learning to build data‐driven models for unknown long time dynamics - Applications in cardiovascular modeling, International Journal for Numerical Methods in Biomedical Engineering (2021).

Author

Francesco Regazzoni, MOX - Politecnico di Milano (francesco.regazzoni@polimi.it)

Ackowledgements

  • Luca Dede', for having provided the code of the lbfgs.m optimization function.
  • Primoz Cermelj, for the inifile.m utility.

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