A list of awesome papers and cool resources on transfer learning, domain adaptation and domain-to-domain translation in general! As you will notice, this list is currently mostly focused on domain adaptation (DA) and domain-to-domain translation, but don't hesitate to suggest resources in other subfields of transfer learning.
Note: this list is not actively maintained anymore, but I still accept pull requests, so please don't hesitate if you want to contribute with newer resources
Papers are ordered by theme and inside each theme by publication date (submission date for arXiv papers). If the network or algorithm is given a name in a paper, this one is written in bold before the paper's name.
Transfer of deep learning models.
Transfer between a source and a target domain. In unsupervised domain adaptation, only the source domain can have labels.
All the source points are labelled, but only few target points are.
Only a few target examples are available, but they are labelled
Domain adaptation applied to other fields
The results are indicated as the prediction accuracy (in %) in the target domain after adapting the source to the target. For the moment, they only correspond to the results given in the original papers, so the methodology may vary between each paper and these results must be taken with a grain of salt.