Machine Learning (ML) has a great potential to improve radio networks, however, it does not provide insights to humans on its strategies. This is one of the barriers to the wide adoption of ML. ML interpretability can help to overcome this barrier, by making black-box models explainable.


For further information, please feel free to contact the project manager, Prof. Andreas Mitschele-Thiel or the responsible person in the group, M. Sc. Faiaz Nazmetdinov.