The model-learning documentation

model-learning is a library for model learning and model reduction, written in MATLAB. The main methods and algorithms implemented in the library have been introduced in the papers [1,2], wherein they are derived and documented.

Contents

• Installation
• Python wrapper
  • Option 1: Install the library by setuptools
  • Option 2: Add the library path to Python paths
  • Option 3: Add the library path within your python script
• Quickstart
• Notes about the conventions
  • Function arguments
  • Variable names
• Tutorial
  • Learning models without inter-individual variability
  • Learning models with inter-individual variability
• Documentation
  • The folder example
  • The struct problem
  • The struct model
  • The struct test
  • The struct dataset

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)

Indices and tables

• Index

• Module Index

• Search Page