Lecturers Jakob Hoydis (left) and Sebastian Cammerer (right)

Revised DLACOM lecture this summer semester

March 29, 2022 /

In the coming summer semester (SS22) there will be a revised Deep Learning Applications for Communications (DLACOM) lecture given by renowned scientists in the field from Nvidia research.

Revised DLACOM lecture in SS22

Deep Learning Applications for Communications (DLACOM)

first started as a brand new lecture in 2018. Back then the idea of guest lecturer Dr.-Ing. Jakob Hoydis was to give an introduction to the emerging topic of deep learning for the field of (wireless) communications. The lecture thereby focused on selected topics of recent state-of-the-art research and added interactive code examples for each of the discussed applications.

Revised lecture and new framework

Now, after four successful years of DLACOM, Dr. Hoydis and his colleagues at NVIDIA research are revising the lecture. As deep learning for the PHY layer became not just one of the hottest research areas in the field of communications but also a new study item of 3GPP for the future 6G mobile communications standard, many new and exciting findings emerged which are now integrated into the new lecture. The updated lecture will also feature new and more advanced code examples which will all be based on the same framework: the just recently released open-source TensorFlow-based library Sionna.

So if you are interested in state-of-the-art applications of deep learning in communications lectured by renowned scientists of the field, have a look at:

Lecture: DLACOM C@mpus, Website
Lecturers: Dr.-Ing. Jakob Hoydis, Dr.-Ing. Fayçal Aït Aoudia and Dr.-Ing. Sebastian Cammerer
Support: Sebastian Dörner, Jannis Clausius, Prof. Dr.-Ing. Stephan ten Brink
When: Thursdays 14:00 -15:30, first date 14th April
Where: PWR 47 - INÜ-Hörsaal (PF47/02/2.314)
Info: 2 SWS, 3 ECTS
This course is intended for master students focusing on communications and/or information sciences (recommended but not required: course on information theory, communications I-III, deep learning).

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