Director:  Prof. Dr. Bernhard Schölkopf Secretary:  Sabrina Nielebock

The department studies theory and applications of statistical learning. Examples thereof are the design of new machine learning algorithms, the study and modeling of perceptual tasks performed by animate visual systems, and the application of machine learning methods to problems ranging from computer vision to bioinformatics.

Department Overview Project Reports: Statistical Learning Theory Kernel Algorithms Causal and Probabilistic Inference Vision and Image Processing Robot Learning Machine Learning in Neuroscience Bioinformatics

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