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Free Deep Learning Resources

Video Lectures

There is a high demand for free resources concerning deep learning. For this reason, we decided to host our lecture video recordings online. Note that the lecture is adapted each semester to incorporate the latest state-of-the-art.

Opens external link in new windowVideo Lecture Summer 2018

Opens external link in new windowVideo Lecture Winter 2018/2019

Opens external link in new windowVideo Lecture Summer 2019

 

 

Supplementary Documents

Furthermore, we have a short summary of the most important parts of the lecture hosted as Opens external link in new windowintroduction to deep learning. Note that this document is only supplementary material to the lecture and does not contain enough information to pass the oral exam.

Note that the material is licensed under Creative Commons 4.0 Attribution License. Feel free to share and reuse!

 

 

Programming Exercises

Another excellent supplementary material are the iPython Notebooks that we created for the MICCAI Educational Challenge 2018. They are available for download at Opens external link in new windowGitHub

 

 

Introduction to Deep Learning Computed Tomography & Known Operator Learning

Use "pip install pyronn" to install.

We created this material to make access to deep learning image reconstruction and known operator learning as easy as possible. The theory including a refresher on deep learning and reconstruction basics is found in the first presentation Initiates file downloadDeep Learning Computed Tomography & Known Operator Learning Theory. Next, we prepared an introduction to PYRO-NN and its concepts in Initiates file downloadIntroduction PYRO-NN. Finally, we give extended comments to example code in Initiates file downloadCoding Examples using PYRO-NN. Same code is also available online to experiment & modify in our Opens external link in new windowOnline PYRO-NN Experimentation Environment.

Initiates file downloadDeep Learning Computed Tomography & Known Operator Learning Theory

Initiates file downloadIntroduction PYRO-NN

Initiates file downloadCoding Examples using PYRO-NN

Opens external link in new windowOnline PYRO-NN Experimentation Environment