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Information Theoretic Limits of Deep Learning


Prof. Dr. Grégoire Montavon, Prof. Dr. Giuseppe Caire

In this agility project we consider deep learning as a machinery for fine-tuning, enhancing or completely replacing various traditional algorithms in communications based on signal processing and information theory. For example, we utilise deep learning for large-scale channel estimation in wireless networks, simultaneous communication and tracking, or sparse recovery problems. Furthermore, to address new requirements for compression and communication of multimedia signals in future machine-to-machine type scenarios, we consider deep-learning based codecs for IoT applications.

Prof. Dr. Grégoire Montavon

Research Group Lead

Dr. Osman Musa Bifold researcher

Dr. Osman Musa

Postdoctoral Researcher