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71 Publications
2021 | Conference Paper | IST-REx-ID: 14176 | 
Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. Neighborhood contrastive learning applied to online patient monitoring. In: Proceedings of 38th International Conference on Machine Learning. Vol 139. ML Research Press; 2021:11964-11974.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 14182 |
Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler P. Backward-compatible prediction updates: A probabilistic approach. In: 35th Conference on Neural Information Processing Systems. Vol 34. ; 2021:116-128.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 14181 |
Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. Boosting variational inference with locally adaptive step-sizes. In: Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence; 2021:2337-2343. doi:10.24963/ijcai.2021/322
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| arXiv
2021 | Conference Paper | IST-REx-ID: 14179 |
Kügelgen J von, Sharma Y, Gresele L, et al. Self-supervised learning with data augmentations provably isolates content from style. In: Advances in Neural Information Processing Systems. Vol 34. ; 2021:16451-16467.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 14180 |
Rahaman N, Gondal MW, Joshi S, et al. Dynamic inference with neural interpreters. In: Advances in Neural Information Processing Systems. Vol 34. ; 2021:10985-10998.
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| arXiv
2021 | Journal Article | IST-REx-ID: 14117 |
Scholkopf B, Locatello F, Bauer S, et al. Toward causal representation learning. Proceedings of the IEEE. 2021;109(5):612-634. doi:10.1109/jproc.2021.3058954
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2021 | Conference Paper | IST-REx-ID: 14178 |
Dittadi A, Träuble F, Locatello F, et al. On the transfer of disentangled representations in realistic settings. In: The Ninth International Conference on Learning Representations. ; 2021.
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| arXiv
2021 | Preprint | IST-REx-ID: 14221 |
Locatello F. Enforcing and discovering structure in machine learning. arXiv. doi:10.48550/arXiv.2111.13693
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| arXiv
2021 | Conference Paper | IST-REx-ID: 14332
Träuble F, Dittadi A, Wuthrich M, et al. Representation learning for out-of-distribution generalization in reinforcement learning. In: ICML 2021 Workshop on Unsupervised Reinforcement Learning. ; 2021.
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2020 | Journal Article | IST-REx-ID: 14125 |
Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired feature sets. Bioinformatics. 36(Supplement_2), i919–i927.
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2020 | Conference Paper | IST-REx-ID: 14186 |
Locatello F, Bauer S, Lucic M, et al. A commentary on the unsupervised learning of disentangled representations. In: The 34th AAAI Conference on Artificial Intelligence. Vol 34. Association for the Advancement of Artificial Intelligence; 2020:13681-13684. doi:10.1609/aaai.v34i09.7120
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| arXiv
2020 | Conference Paper | IST-REx-ID: 14188 |
Locatello F, Poole B, Rätsch G, Schölkopf B, Bachem O, Tschannen M. Weakly-supervised disentanglement without compromises. In: Proceedings of the 37th International Conference on Machine Learning. Vol 119. ; 2020:6348–6359.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 14187 |
Négiar G, Dresdner G, Tsai A, et al. Stochastic Frank-Wolfe for constrained finite-sum minimization. In: Proceedings of the 37th International Conference on Machine Learning. Vol 119. ; 2020:7253-7262.
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2020 | Journal Article | IST-REx-ID: 14195 |
Locatello F, Bauer S, Lucic M, et al. A sober look at the unsupervised learning of disentangled representations and their evaluation. Journal of Machine Learning Research. 2020;21.
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| arXiv
2020 | Conference Paper | IST-REx-ID: 14326 |
Locatello F, Weissenborn D, Unterthiner T, et al. Object-centric learning with slot attention. In: Advances in Neural Information Processing Systems. Vol 33. Curran Associates; 2020:11525-11538.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 14184 |
Locatello F, Tschannen M, Bauer S, Rätsch G, Schölkopf B, Bachem O. Disentangling factors of variation using few labels. In: 8th International Conference on Learning Representations. ; 2019.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 14189 |
Gresele L, Rubenstein PK, Mehrjou A, Locatello F, Schölkopf B. The incomplete Rosetta Stone problem: Identifiability results for multi-view nonlinear ICA. In: Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence. Vol 115. ML Research Press; 2019:217-227.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 14197 |
Locatello F, Abbati G, Rainforth T, Bauer S, Schölkopf B, Bachem O. On the fairness of disentangled representations. In: Advances in Neural Information Processing Systems. Vol 32. ; 2019:14611–14624.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 14191 |
Locatello F, Yurtsever A, Fercoq O, Cevher V. Stochastic Frank-Wolfe for composite convex minimization. In: Advances in Neural Information Processing Systems. Vol 32. ; 2019:14291–14301.
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| arXiv
2019 | Conference Paper | IST-REx-ID: 14193 |
Steenkiste S van, Locatello F, Schmidhuber J, Bachem O. Are disentangled representations helpful for abstract visual reasoning? In: Advances in Neural Information Processing Systems. Vol 32. ; 2019.
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| arXiv