BIBLIOGRAPHY 135 Liu, X., Sanchez, P., Thermos, S., O’Neil, A. Q., and Tsaftaris, S. A. (2022). Learning Disentangled Representations in the Imaging Domain. Medical Image Analysis. (Cited on page 15.) Locatello, F., Bauer, S., Lucie, M., Rätsch, G., Gelly, S., Schölkopf, B., and Bachem, O. (2018). Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations. 36th International Conference on Machine Learning, ICML 2019, 2019-June:7247–7283. (Cited on pages 6, 17, 72, 76, 79, 106, 108, and 114.) Locatello, F., Poole, B., Rätsch, G., Schölkopf, B., Bachem, O., and Tschannen, M. (2020). Weakly-Supervised Disentanglement Without Compromises. 37th International Conference on Machine Learning, ICML 2020, PartF1681479:6304–6315. (Cited on pages 7, 18, and 76.) Lu, Y. and Xu, P. (2018). Anomaly Detection for Skin Disease Images Using Variational Autoencoder. arXiv preprint arxiv.1807.01349. (Cited on page 28.) Mathieu, E., Rainforth, T., Siddharth, N., and Teh, Y. W. (2018). Disentangling Disentanglement in Variational Autoencoders. 36th International Conference on Machine Learning, ICML 2019, 2019-June:7744–7754. (Cited on page 17.) Matthey, L., Higgins, I., Hassabis, D., and Lerchner, A. (2017). dSprites: Disentanglement testing Sprites dataset. https://github.com/deepmind/dspritesdataset/. (Cited on page 111.) Montero, M. L., Ludwig, C. J. H., Ponte Costa, R., Malhotra, G., and Bowers, J. S. (2021). The role of Disentanglement in Generalisation. InInternational Conference on Learning Representations (ICLR). (Cited on pages 106, 109, 112, 115, 118, and 125.) Nalisnick, E., Matsukawa, A., Teh, Y. W., Gorur, D., and Lakshminarayanan, B. (2018). Do Deep Generative Models Know What They Don’t Know? 7th International Conference on Learning Representations, ICLR 2019. (Cited on page 126.) Nene, S. A., Nayar, S. K., and Murase, H. (1996). Columbia Object Image Library (COIL-100). Technical Report CUCS-006-96. (Cited on pages 72 and 74.) Painter, M., Hare, J., and Prügel-Bennett, A. (2020). Linear Disentangled Representations and Unsupervised Action Estimation. Advances in Neural Information Processing Systems, 2020-December. (Cited on pages 7, 52, 58, 59, 81, 84, and109.)
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