2 citations · 4 across the 3 of their papers we have counts for
3 papers
cs.CV2022★ 2 cited
Transfer Learning for Segmentation Problems: Choose the Right Encoder and Skip the Decoder
Jonas Dippel, Matthias Lenga, Thomas Goerttler +2
It is common practice to reuse models initially trained on different data to increase downstream task performance. Especially in the computer vision domain, ImageNet-pretrained wei…
cs.LG2022★ 1 cited
Similarity of Pre-trained and Fine-tuned Representations
Thomas Goerttler, Klaus Obermayer
In transfer learning, only the last part of the networks - the so-called head - is often fine-tuned. Representation similarity analysis shows that the most significant change still…
cs.LG2021★ 1 cited
Exploring the Similarity of Representations in Model-Agnostic Meta-Learning
Thomas Goerttler, Klaus Obermayer
In past years model-agnostic meta-learning (MAML) has been one of the most promising approaches in meta-learning. It can be applied to different kinds of problems, e.g., reinforcem…