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Self-supervised learning with data augmentations provably isolates content from style
@conference{Kugelenetal21, title = {Self-supervised learning with data augmentations provably isolates content from style}, booktitle = {Advances in Neural Information Processing Systems 34 (NeurIPS 2021)}, pages = {16451--16467}, editors = {M. Ranzato and A. Beygelzimer and Y. Dauphin and P.S. Liang and J. Wortman Vaughan}, publisher = {Curran Associates, Inc.}, month = dec, year = {2021}, note = {*equal contribution}, slug = {kugelenetal21}, author = {von K{\"u}gelgen*, J. and Sharma*, Y. and Gresele*, L. and Brendel, W. and Sch{\"o}lkopf, B. and Besserve, M. and Locatello, F.}, url = {https://proceedings.neurips.cc/paper/2021/file/8929c70f8d710e412d38da624b21c3c8-Paper.pdf}, month_numeric = {12} }