{"volume":34,"intvolume":"        34","year":"2020","conference":{"name":"AAAI: Conference on Artificial Intelligence","start_date":"2020-02-07","location":"New York, NY, United States","end_date":"2020-02-12"},"citation":{"short":"F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, in:, The 34th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2020, pp. 13681–13684.","ama":"Locatello F, Bauer S, Lucic M, et al. A commentary on the unsupervised learning of disentangled representations. In: <i>The 34th AAAI Conference on Artificial Intelligence</i>. Vol 34. Association for the Advancement of Artificial Intelligence; 2020:13681-13684. doi:<a href=\"https://doi.org/10.1609/aaai.v34i09.7120\">10.1609/aaai.v34i09.7120</a>","ista":"Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2020. A commentary on the unsupervised learning of disentangled representations. The 34th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 34, 13681–13684.","chicago":"Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, and Olivier Bachem. “A Commentary on the Unsupervised Learning of Disentangled Representations.” In <i>The 34th AAAI Conference on Artificial Intelligence</i>, 34:13681–84. Association for the Advancement of Artificial Intelligence, 2020. <a href=\"https://doi.org/10.1609/aaai.v34i09.7120\">https://doi.org/10.1609/aaai.v34i09.7120</a>.","apa":"Locatello, F., Bauer, S., Lucic, M., Rätsch, G., Gelly, S., Schölkopf, B., &#38; Bachem, O. (2020). A commentary on the unsupervised learning of disentangled representations. In <i>The 34th AAAI Conference on Artificial Intelligence</i> (Vol. 34, pp. 13681–13684). New York, NY, United States: Association for the Advancement of Artificial Intelligence. <a href=\"https://doi.org/10.1609/aaai.v34i09.7120\">https://doi.org/10.1609/aaai.v34i09.7120</a>","ieee":"F. Locatello <i>et al.</i>, “A commentary on the unsupervised learning of disentangled representations,” in <i>The 34th AAAI Conference on Artificial Intelligence</i>, New York, NY, United States, 2020, vol. 34, no. 9, pp. 13681–13684.","mla":"Locatello, Francesco, et al. “A Commentary on the Unsupervised Learning of Disentangled Representations.” <i>The 34th AAAI Conference on Artificial Intelligence</i>, vol. 34, no. 9, Association for the Advancement of Artificial Intelligence, 2020, pp. 13681–84, doi:<a href=\"https://doi.org/10.1609/aaai.v34i09.7120\">10.1609/aaai.v34i09.7120</a>."},"language":[{"iso":"eng"}],"_id":"14186","doi":"10.1609/aaai.v34i09.7120","page":"13681-13684","author":[{"orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","last_name":"Locatello","first_name":"Francesco"},{"last_name":"Bauer","first_name":"Stefan","full_name":"Bauer, Stefan"},{"first_name":"Mario","last_name":"Lucic","full_name":"Lucic, Mario"},{"full_name":"Rätsch, Gunnar","last_name":"Rätsch","first_name":"Gunnar"},{"last_name":"Gelly","first_name":"Sylvain","full_name":"Gelly, Sylvain"},{"last_name":"Schölkopf","first_name":"Bernhard","full_name":"Schölkopf, Bernhard"},{"full_name":"Bachem, Olivier","first_name":"Olivier","last_name":"Bachem"}],"publication":"The 34th AAAI Conference on Artificial Intelligence","publication_identifier":{"isbn":["9781577358350"],"eissn":["2374-3468"]},"external_id":{"arxiv":["2007.14184"]},"status":"public","quality_controlled":"1","title":"A commentary on the unsupervised learning of disentangled representations","date_created":"2023-08-22T14:07:26Z","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa":1,"oa_version":"Preprint","scopus_import":"1","publisher":"Association for the Advancement of Artificial Intelligence","issue":"9","date_published":"2020-07-28T00:00:00Z","publication_status":"published","extern":"1","main_file_link":[{"url":"https://arxiv.org/abs/2007.14184","open_access":"1"}],"abstract":[{"text":"The goal of the unsupervised learning of disentangled representations is to\r\nseparate the independent explanatory factors of variation in the data without\r\naccess to supervision. In this paper, we summarize the results of Locatello et\r\nal., 2019, and focus on their implications for practitioners. We discuss the\r\ntheoretical result showing that the unsupervised learning of disentangled\r\nrepresentations is fundamentally impossible without inductive biases and the\r\npractical challenges it entails. Finally, we comment on our experimental\r\nfindings, highlighting the limitations of state-of-the-art approaches and\r\ndirections for future research.","lang":"eng"}],"department":[{"_id":"FrLo"}],"day":"28","type":"conference","date_updated":"2023-09-12T07:44:48Z","month":"07","article_processing_charge":"No"}