Doctoral students Sebastian Cammerer and Sebastian Dörner will be attending this year's IEEE International Conference on Communications. The conference will be held from May 20-24 in Shanghai, China.
There they will be giving the tutorial 'Deep Learning for Communications: A Hands on Experience'
In the last decade, deep learning has led to many breakthroughs in various domains, such as computer vision, natural language processing, and speech recognition. Motivated by these successes, researchers all over the world have recently started to investigate applications of this tool to their respective domain of expertise, with communications being one of them. The goal of this tutorial is to provide an introduction to deep learning that will enable the attendees to identify potential applications in their own research field. We give an overview of the very rapidly growing body of literature, explain state-of-the-art neural network architectures and training methods, and go through several promising applications and concepts, such as neural decoding, deep MIMO detection and autoencoders. In the second part of this tutorial, we aim to lower the barrier-to-entry for ML-newcomers to enable the implementation of own applications. Therefore, a practical hands-on coding session introduces a state-of-the-art deep learning toolchain by implementing, training and evaluating an autoencoder system in Tensorflow. The attendees receive tutorial slides and Jupyter notebooks containing code examples, which allows them to quickly get up to speed with this new and exciting field. During the break, we demonstrate the world's first fully neural network-based communications system.
Interest in the lecture was so great that a larger room was needed...
(Image: Sebastian Cammerer)