Machine Learning

The main research focus of the Machine Learning group is the theory, methods and applications of deep learning. This includes an information-theoretical analysis of deep representations, the development of efficient data analysis techniques and novel deep architectures as well as the use of state-of-the-art neural network models for classification and regression tasks on image, text, video and time series data. Timely research topics such as explainable artificial intelligence (XAI), interpretable and reliable machine learning, compression of neural networks or the convergence between machine learning and communications are also investigated by the group.

Research Topics

The research topics address different fields in the areas of deep learning, interpretable machine learning, robust signal processing, computer vision and communications.

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Journal papers, conference proceedings, talks and tutorials, standardization contributions and books. Find out about the publications of our group.

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