{"alternative_title":["PMLR"],"title":"Weakly-supervised disentanglement without compromises","quality_controlled":"1","status":"public","scopus_import":"1","oa_version":"Preprint","oa":1,"date_created":"2023-08-22T14:08:14Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","department":[{"_id":"FrLo"}],"abstract":[{"text":"Intelligent agents should be able to learn useful representations by\r\nobserving changes in their environment. We model such observations as pairs of\r\nnon-i.i.d. images sharing at least one of the underlying factors of variation.\r\nFirst, we theoretically show that only knowing how many factors have changed,\r\nbut not which ones, is sufficient to learn disentangled representations.\r\nSecond, we provide practical algorithms that learn disentangled representations\r\nfrom pairs of images without requiring annotation of groups, individual\r\nfactors, or the number of factors that have changed. Third, we perform a\r\nlarge-scale empirical study and show that such pairs of observations are\r\nsufficient to reliably learn disentangled representations on several benchmark\r\ndata sets. Finally, we evaluate our learned representations and find that they\r\nare simultaneously useful on a diverse suite of tasks, including generalization\r\nunder covariate shifts, fairness, and abstract reasoning. Overall, our results\r\ndemonstrate that weak supervision enables learning of useful disentangled\r\nrepresentations in realistic scenarios.","lang":"eng"}],"main_file_link":[{"url":"https://arxiv.org/abs/2002.02886","open_access":"1"}],"date_published":"2020-07-07T00:00:00Z","publication_status":"published","extern":"1","month":"07","article_processing_charge":"No","date_updated":"2023-09-12T07:59:29Z","type":"conference","day":"07","year":"2020","intvolume":"       119","volume":119,"_id":"14188","language":[{"iso":"eng"}],"conference":{"name":"International Conference on Machine Learning","start_date":"2020-07-13","location":"Virtual","end_date":"2020-07-18"},"citation":{"short":"F. Locatello, B. Poole, G. Rätsch, B. Schölkopf, O. Bachem, M. Tschannen, in:, Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 6348–6359.","ama":"Locatello F, Poole B, Rätsch G, Schölkopf B, Bachem O, Tschannen M. Weakly-supervised disentanglement without compromises. In: <i>Proceedings of the 37th International Conference on Machine Learning</i>. Vol 119. ; 2020:6348–6359.","apa":"Locatello, F., Poole, B., Rätsch, G., Schölkopf, B., Bachem, O., &#38; Tschannen, M. (2020). Weakly-supervised disentanglement without compromises. In <i>Proceedings of the 37th International Conference on Machine Learning</i> (Vol. 119, pp. 6348–6359). Virtual.","chicago":"Locatello, Francesco, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, and Michael Tschannen. “Weakly-Supervised Disentanglement without Compromises.” In <i>Proceedings of the 37th International Conference on Machine Learning</i>, 119:6348–6359, 2020.","ista":"Locatello F, Poole B, Rätsch G, Schölkopf B, Bachem O, Tschannen M. 2020. Weakly-supervised disentanglement without compromises. Proceedings of the 37th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 119, 6348–6359.","ieee":"F. Locatello, B. Poole, G. Rätsch, B. Schölkopf, O. Bachem, and M. Tschannen, “Weakly-supervised disentanglement without compromises,” in <i>Proceedings of the 37th International Conference on Machine Learning</i>, Virtual, 2020, vol. 119, pp. 6348–6359.","mla":"Locatello, Francesco, et al. “Weakly-Supervised Disentanglement without Compromises.” <i>Proceedings of the 37th International Conference on Machine Learning</i>, vol. 119, 2020, pp. 6348–6359."},"external_id":{"arxiv":["2002.02886"]},"author":[{"orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","first_name":"Francesco","last_name":"Locatello"},{"full_name":"Poole, Ben","first_name":"Ben","last_name":"Poole"},{"first_name":"Gunnar","last_name":"Rätsch","full_name":"Rätsch, Gunnar"},{"full_name":"Schölkopf, Bernhard","last_name":"Schölkopf","first_name":"Bernhard"},{"full_name":"Bachem, Olivier","first_name":"Olivier","last_name":"Bachem"},{"full_name":"Tschannen, Michael","first_name":"Michael","last_name":"Tschannen"}],"publication":"Proceedings of the 37th International Conference on Machine Learning","page":"6348–6359"}