Deep Learning and Artificial Intelligence (WS 2019/20)
News
- [18.03.2020] Due to the corona pandemic the additional exam on 06.04 is canceled.
- [12.03.2020] Following the instructions from the ministry, all teaching operations (i.e. exam inspections, exams, lectures, etc.) are suspended until further notice. That means that we can not make any definitive statements about whether or when additional exams/courses/exam inspections will take place. Please refrain from sending individual Emails asking for more information, as we don’t know how things will develop ourselves. We will keep you posted and let you know as soon as we get any new instructions from above. Please also refer to: https://www.uni-muenchen.de/aktuelles/corona_informationen/index.html . Thanks and sorry for the inconvenience!
- [19.11.2019] The date for the final exam is now set: Feb 19 2020 at 4 p.m. (16:00 Uhr) Details see below.
- Slides for the lecture, exercise sheets and other material will be published exclusively by https://uni2work.ifi.lmu.de/course/W19/IfI/DL&AI
- [26.09.2019] The registration for the course via Uni2Work is now open: https://uni2work.ifi.lmu.de/course/W19/IfI/DL&AI
Organisation
- Umfang: 3+2 hours weekly (equals 6 ECTS)
- Responsible Professor: Prof. Dr. Matthias Schubert
- Lecturers: Dr. Florian Büttner, Pankaj Gupta, Dr. Denis Krompass, Prof. Dr. Matthias Schubert,
Dr. Sigurd Spieckermann, Prof. Dr. Volker Tresp, Dr. Yinchong Yang
- Assistants: Sabrina Friedl
- Required: Lecture "Machine Learning" or equivalent, Lecture "Knowledge Discovery in Databases I" or equivalent
- Audience: The lecture is directed towards Master students in Mediainformatics, Bioinformatics, Informatics, and Data Science
Final Exam
When: Wed, Feb 19 2020, 4 p.m. - 6 p.m. (16:00 -- 18:00 Uhr) sine tempore!>
Where: Main Building B 101
Registration: Uni2Work
Allowed aids: Two sheets of Din A4 paper with handwritten notes on both sides, calculator
Additional Exam
When: tbd
Where: tbd
Registration: tbd
Allowed aids: Two sheets of Din A4 paper with handwritten notes on both sides, calculator
Time and Locations
All times are c.t. (cum tempore)
Component | When | Where | Starts at |
Lecture | Wed, 13.00 - 16.00 h | Room S 004 (Schellingstr. 3) | 16.10.2019 |
Tutorial 1 | Mo, 14.00 - 16.00 h | Room R 051 (Schellingstr. 3) | 21.10.2019 |
Tutorial 2 | Mo 16.00 - 18.00 h | Room R 051 (Schellingstr. 3) | 21.10.2019 |
Content
During the last decade the availability of large amounts of data and the strong increase in computing power allowed a renaissance of neural networks and advanced planning techniques for independent agents. Whereas the area of deep learning extended well established neural network technology to allow a whole new level of data transformation, modern reinforcement learning techniques yield the artificial backbone for intelligent assistant systems and autonomous vehicles.
The course starts with an introduction to neural networks and explains the developments that led to deep architectures. Furthermore, the course gives an introduction to advanced planning techniques and how they can be trained using deep neural networks and other machine learning technologies.
Course Schedule
Lecture | Tutorial | |
---|---|---|
Date | Topic | Date |
16.10.2019 | Introduction Speaker: Sigurd Spieckermann |
21.10.2019 |
23.10.2019 | Basic Neural Networks Speaker: Yinchong Yang |
28.10.2019 |
30.10.2019 | Training Neural Networks Speaker: Sigurd Spieckermann |
04.11.2019 |
06.11.2019 | Deep Learning Tools Speaker: Denis Krompass |
11.11.2019 |
13.11.2019 | Convolutional Neural Networks Speaker: Denis Krompass |
18.11.2019 |
20.11.2019 | Recurrent Neural Networks Speaker: Pankaj Gupta |
25.11.2019 |
27.11.2019 | Deep Learning and Uncertainty Speaker: Florian Büttner |
02.12.2019 |
04.12.2019 | Representation and Distributional Learning Speaker: Pankaj Gupta |
09.12.2019 |
11.12.2019 | Generative Models Speaker: Yinchong Yang |
16.12.2019 |
18.12.2019 | Sequential Decision Problems and Autonomous Agents Speaker: Matthias Schubert |
07.01.2020 |
08.01.2020 | Model-free Reinforcement Learning Speaker: Matthias Schubert |
13.01.2020 |
15.01.2020 | Value Function Approximation Speaker: Matthias Schubert |
20.01.2020 |
22.01.2020 | Policy Gradients and Actor Critic Learning Speaker: Ma tthias Schubert |
27.01.2020 |
29.01.2020 | Knowledge Graphs in AI Speaker: Volker Tresp |
03.02.2020 |
05.02.2020 | Q&A | ---------------- |