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This is a short tutorial on applications of PyTorch in computational workflows making use of accelerated numerics and automatic differentiation. Here we look into analyzing and solving inverse problems as a case study.

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PyTorch tutorial @ MAC-MIGS-Amsterdam/Utrecht Workshop, 5 Sep 2024

This is a short tutorial on applications of PyTorch in computational workflows making use of accelerated numerics and automatic differentiation. Here we look into analyzing and solving inverse problems as a case study.

You can run the notebooks for the tutorial on Google Colab using the following links:

Open In Colab Part 1: PyTorch basics

Open In Colab Part 2: Automatic differentiation

Open In Colab Part 3: Inverse problems

Alternatively, you can run the notebooks locally provided you have PyTorch, scikit-image, and Matplotlib Python packages installed.

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This is a short tutorial on applications of PyTorch in computational workflows making use of accelerated numerics and automatic differentiation. Here we look into analyzing and solving inverse problems as a case study.

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