1. Alber, M., et al.: innvestigate neural networks. J. Mach. Learn. Res. 20(93), 1–8 (2019)
2. Bello, I., Zoph, B., Vaswani, A., Shlens, J., Le, Q.V.: Attention augmented convolutional networks. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 3286–3295 (2019)
3. Budd, S., Robinson, E.C., Kainz, B.: A survey on active learning and human-in-the-loop deep learning for medical image analysis. Med. Image Anal. 71, 102062 (2021)
4. Cardoso, J., et al.: Interpretable and Annotation-Efficient Learning for Medical Image Computing Third International Workshop, iMIMIC 2020, Second International Workshop, MIL3ID 2020, and 5th International Workshop, Labels 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, 4–8 October 2020, Proceedings (2020)
5. Chen, T., Kornblith, S., Norouzi, M., Hinton, G.: A simple framework for contrastive learning of visual representations. In: International Conference on Machine Learning, pp. 1597–1607. PMLR (2020)