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Hybrid Modeling Tutorial

Hybrid Modeling is a modeling technique in which a physics-based model is combined with a data-based approach. By combining the best of both worlds, we trade off the benefit of prior knowledge when training data is scarce with the flexibility of a data-driven approaches when training data is abundant. In this notebook we demonstrate the power of hybrid modeling by modeling data, which roughly follows the amplitude of a non-linearly damped oscillator with missing data.

The paper Hybrid Modeling Design Patterns (Maja Rudolph, Stefan Kurz, Barbara Rakitsch) provides additional context and background to this notebook, as well as a broader perspective on the topic.

Purpose of the Project

This software is a tutorial, solely developed for educational purpose. It will neither be maintained nor monitored in any way.

Installation Guidelines

First create a conda environment

conda create -n HYM_notebook python=3.11

Activate the environment

conda activate HYM_notebook

Install packages from requirements file using conda

pip install -r requirements.txt

Trouble Shooting

If you have problems, importing the packages in Jupyter, add your Conda environment to Jupyter as a new kernel.

python -m ipykernel install --user --name=HYM_notebook --display-name "HYM notebook"

Open Jupyter, go to Kernel > Change Kernel and select "HYM notebook".

License

Benchmarks is open-sourced under the MIT license. See the LICENSE file for details.

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