Deep learning is the tool for our research to obtain learned representations, fit functions such as policies or value functions and learn internal models. Along the way of using deep learning techniques for our core focus of autonomous learning we frequently need to develop new methods. Quite often, we stumble upon unsolved or puzzling problems in the techniques themselves. Some of which we are solving, see our projects below. In general, we are particularly interested in techniques for representation learning, internal model learning and continual learning.
