Advanced Deep Learning
Prof. Dr. Abhinav Valada, Dr. Daniele Cattaneo
Co-Organizers:
Martin Büchner, Markus Käppeler, Maximilian Luz, Rohit Mohan
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: | Wednesday, 14:00-16:00 First meeting on April 17th 2024. |
| Location: | This course will be taught in person. Weekly teaching will be held on Wednesday 14:00-16:00 at HS 00 006 (G.-Köhler-Allee 082). Exercise sessions will take place on Friday 12:00-14:00 at HS 00 006 (G.-Köhler-Allee 082) |
| Learning Platform: | ILIAS |
| Prerequisites: | Students must have completed a graded course equivalent to Foundations of Deep Learning |
Course Overview
The course will be taught in English
Every week there will be:
- an in-person lecture (Wednesdays, 14:00-16:00)
- an exercise sheet
- an in-person exercise session (Fridays 12:00 - 14:00)
At the end, there will be an oral exam.
Course Schedule
The following are the dates for the in-person lectures:
17.04.24 – Lecture 1: Introduction
24.04.24 – Lecture 2: Multidimensional Deep Learning
08.05.24 – Lecture 3: Transformers
15.05.24 – No Lecture
29.05.24 – Lecture 4: Graph Neural Networks
05.06.24 – Lecture 5: Similarity Learning
12.06.24 – Lecture 6: Multimodal Deep Learning
19.06.24 – Lecture 7: Self-Supervised Learning and Foundation Models
26.06.24 – Lecture 8: Guest Lecture - Dr. Oezguen Cicek (Bosch): "Multi-Modal AI-Based Perception for Autonomous Driving"
03.07.24 – Lecture 9: Transfer Learning, Domain Adaptation, and Continual Learning
10.07.24 – Lecture 10: Generative Models
17.07.24 – Lecture 11: Round-up / Exam Q & A
In the first session (on 17.04.24) you will get additional information about the course and get the opportunity to ask general questions.
IMPORTANT: For this semester, we can only accept a limited number of students for this course. During the first session, we will clarify which prerequisites are required, and we will ask students without appropriate prerequisites to de-register from the course. If you are on the waiting-list, please attend the first lecture on 17.04.2024, as some spots might become available.
Questions?
If you have a question, please post it in the ILIAS forum (so everyone can benefit from the answer).