Written Assignments
Installation and Introduction to Python and Tensorflow |
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Gradient Decent |
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Logistic Regression and Ising Hamiltonian (without Susy) |
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Feed Forward Deep Neural Networks (Ising Hamiltonian) |
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Convolutional Networks, High-Level Concepts |
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Energy Based Models, Boltzmann Learning |
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Restricted Boltzmann Machines |
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STM Machine Learning |
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Variational Autoencoders and Generative Adversarial Networks |
Talks
Talks take place Wednesdays 15:15-16:00 via Zoom.13.05.2020, 15:15 |
Daniil Kudrin Installation and Introduction to Python and Tensorflow |
PDF 1 | PDF 2 | |
20.05.2020, 15:15 |
Krish Ramesh Gradient Decent |
Slides | Code | Video |
27.05.2020, 15:15 |
Javier Pasarin Lopez Logistic Regression and Ising Hamiltonian (without Susy) |
Slides | Code | Video |
03.06.2020, 15:15 |
Felix Puster Feed Forward Deep Neural Networks (Ising Hamiltonian) |
Slides | Code | Video |
10.06.2020, 15:15 |
Max Staats Convolutional Networks, High-Level Concepts |
Slides | Code | Video |
17.06.2020, 15:15 |
Sebastian Bürger Energy Based Models, Boltzmann Learning |
Slides | Video | |
24.06.2020, 15:15 |
Camila Bräutigam Restricted Boltzmann Machines |
Slides | Code | Video |
08.07.2020, 15:15 |
Stefan Tsankov STM Machine Learning |
Slides | Video | |
15.07.2020, 15:15 |
Caspar Pirker Variational Autoencoders and Generative Adversarial Networks |
Slides | Video |