Kursinformation

While deep learning models have achieved outstanding performances on various tasks, those tasks are mostly performed within a certain domain and deep learning models still lack the ability for out of domain generalization.
Here Domain Adaptation and Transfer comes into play. Domain Adaptation and Transfer aim to train models which are not only able to perform in their trained domain but are also able to solve tasks outside of their trained domain.
The techniques for Domain Adaptation and Transfer vary a lot and have impact on several deep learning topics, such as model robustness or neural architecture search.