Deep Learning in Computational Mechanics: An Introductory Course (supplementary material)

• This repository contains the supplementary material of the textbook:

Deep Learning in Computational Mechanics: An Introductory Course (Second Edition), Leon Herrmann, Moritz Jokeit, Oliver Weeger, and Stefan Kollmannsberger, Springer 2025, ISBN: 978-3-031-89528-9, URL: link.springer.com/book/9783031895289

• The material consists of exercises (as Jupyter notebooks and Python files) described in the book (exercises), short demos (as Jupyter notebooks) covered in the book (demos), and lecture slides (as PowerPoint and pdf files) (slides).

Installation

1. Download the repository - either with git clone or the "Download ZIP" button online
2. from the command line, enter that directory with cd exercises
3. run: conda env create -f environment.yml this will create a new environment named aicome
4. activate with conda activate aicome

Quickstart

1. Start jupyter from the command line with: jupyter lab
2. Open a demo .ipynb file and confirm that running it successfully imports packages like torch and cells below run successfully. If so, your environment is ready for all the exercises in the book!

License

Copyright (c) 2024, Leon Herrmann, Moritz Jokeit, Oliver Weeger, Stefan Kollmannsberger, Thomas Hollowell All rights reserved.

All of the material is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0), such that you may reuse and adapt the content for your own purposes as long as appropriate credit is given. Commercial use of the material is prohibited. Any adaptations or derivatives must be shared under the same license.

Contact

In case of questions or the discovery of any bugs, please feel free to reach out to leon.herrmann@uni-weimar.de