Advanced Deep Learning
Prof. Dr. Abhinav Valada1, Dr. Daniele Cattaneo2
Co-Organizers:
Martin Büchner, 3Markus Käppeler, 4Maximilian Luz, 5Rohit Mohan
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Deep learning techniques are constantly evolving and are nowadays recognized as the state-of-the-art solution in many problems in various domains. This course provides you with a good theoretical understanding and practical experience about advanced deep learning techniques and modern architectures include topics in Graph Neural Networks, Multi-dimensional Deep Learning, Transformers, Similarity Learning, Multi-modal Learning, Transfer Learning, Domain Adaptation, Self-supervised Learning, and Generative models. Furthermore, you should be able to use Deep Learning software libraries (PyTorch) in order to work on real-world applications of the content taught.
Details
Time: | Monday, 14:00-16:00 First meeting on April 28th 2025. |
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Location: |
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Learning Platform: | ILIAS7 | |
Prerequisites: | Students must have completed a graded course equivalent to Foundations of Deep Learning8 |
Course Overview
The course will be taught in English
Every week there will be:
- an in-person lecture (Monday, 14:00-16:00)
- an exercise sheet
- an in-person exercise session (Fridays 10:00 - 12:00)
At the end, there will be a written exam.
Course Schedule
The following are the dates for the in-person lectures:
28.04.25 – Lecture 1: Introduction
05.05.25 – Lecture 2: Multidimensional Deep Learning
12.05.25 – Lecture 3: Transformers I
19.05.25 – Lecture 4: Transformers II
26.05.25 – Lecture 5: Graph Neural Networks
02.06.25 – Lecture 6: Similarity Learning
16.06.25 – Lecture 7: Multimodal Deep Learning
23.06.25 – Lecture 8: Self-Supervised Learning and Foundation Models
30.06.25 – Lecture 9: Transfer Learning, Domain Adaptation, and Continual Learning
07.07.25 – Lecture 10: Generative Models
21.07.25 – Lecture 11: Round-up / Exam Q & A
25.07.25 – Lecture 12: Guest Lecture - Dr. Andreas Eitel, Parallel Domain
Neural Simulators for Testing Autonomous Systems
In the first session (on 28.04.25) you will get additional information about the course and get the opportunity to ask general questions.
Questions?
If you have a question, please post it in the ILIAS forum (so everyone can benefit from the answer).