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88 Publications
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2021 | Published | Conference Paper | IST-REx-ID: 14180 | 
Rahaman, Nasim, Muhammad Waleed Gondal, Shruti Joshi, Peter Gehler, Yoshua Bengio, Francesco Locatello, and Bernhard Schölkopf. “Dynamic Inference with Neural Interpreters.” In Advances in Neural Information Processing Systems, 34:10985–98, 2021.
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2021 | Published | Conference Paper | IST-REx-ID: 14181 |
Dresdner, Gideon, Saurav Shekhar, Fabian Pedregosa, Francesco Locatello, and Gunnar Rätsch. “Boosting Variational Inference with Locally Adaptive Step-Sizes.” In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2337–43. International Joint Conferences on Artificial Intelligence, 2021. https://doi.org/10.24963/ijcai.2021/322.
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2021 | Published | Conference Paper | IST-REx-ID: 14182 |
Träuble, Frederik, Julius von Kügelgen, Matthäus Kleindessner, Francesco Locatello, Bernhard Schölkopf, and Peter Gehler. “Backward-Compatible Prediction Updates: A Probabilistic Approach.” In 35th Conference on Neural Information Processing Systems, 34:116–28, 2021.
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| arXiv
2021 | Submitted | Preprint | IST-REx-ID: 14221 |
Locatello, Francesco. “Enforcing and Discovering Structure in Machine Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2111.13693.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14332
Träuble, Frederik, Andrea Dittadi, Manuel Wuthrich, Felix Widmaier, Peter Vincent Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer. “Representation Learning for Out-of-Distribution Generalization in Reinforcement Learning.” In ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021.
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2021 | Patent | IST-REx-ID: 14185 |
Weissenborn, Dirk, Jakob Uszkoreit, Thomas Unterthiner, Aravindh Mahendran, Francesco Locatello, Thomas Kipf, Georg Heigold, and Alexey Dosovitskiy. “Object-Centric Learning with Slot Attention,” 2021.
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| arXiv
2020 | Published | 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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| PubMed | Europe PMC
2020 | Published | Conference Paper | IST-REx-ID: 14186 |
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 The 34th AAAI Conference on Artificial Intelligence, 34:13681–84. Association for the Advancement of Artificial Intelligence, 2020. https://doi.org/10.1609/aaai.v34i09.7120.
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2020 | Published | Conference Paper | IST-REx-ID: 14187 |
Négiar, Geoffrey, Gideon Dresdner, Alicia Tsai, Laurent El Ghaoui, Francesco Locatello, Robert M. Freund, and Fabian Pedregosa. “Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization.” In Proceedings of the 37th International Conference on Machine Learning, 119:7253–62, 2020.
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 14188 |
Locatello, Francesco, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier Bachem, and Michael Tschannen. “Weakly-Supervised Disentanglement without Compromises.” In Proceedings of the 37th International Conference on Machine Learning, 119:6348–6359, 2020.
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2020 | Published | Journal Article | IST-REx-ID: 14195 |
Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, and Olivier Bachem. “A Sober Look at the Unsupervised Learning of Disentangled Representations and Their Evaluation.” Journal of Machine Learning Research. MIT Press, 2020.
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 14326 |
Locatello, Francesco, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran, Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, and Thomas Kipf. “Object-Centric Learning with Slot Attention.” In 34th International Conference on Neural Information Processing Systems, 33:11525–38. Neural Information Processing Systems Foundation, 2020.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14184 |
Locatello, Francesco, Michael Tschannen, Stefan Bauer, Gunnar Rätsch, Bernhard Schölkopf, and Olivier Bachem. “Disentangling Factors of Variation Using Few Labels.” In 8th International Conference on Learning Representations, 2019.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14189 |
Gresele, Luigi, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, and Bernhard Schölkopf. “The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA.” In Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence, 115:217–27. ML Research Press, 2019.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14190 |
Gondal, Muhammad Waleed, Manuel Wüthrich, Đorđe Miladinović, Francesco Locatello, Martin Breidt, Valentin Volchkov, Joel Akpo, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer. “On the Transfer of Inductive Bias from Simulation to the Real World: A New Disentanglement Dataset.” In Advances in Neural Information Processing Systems, Vol. 32, 2019.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14191 |
Locatello, Francesco, Alp Yurtsever, Olivier Fercoq, and Volkan Cevher. “Stochastic Frank-Wolfe for Composite Convex Minimization.” In Advances in Neural Information Processing Systems, 32:14291–14301, 2019.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14193 |
Steenkiste, Sjoerd van, Francesco Locatello, Jürgen Schmidhuber, and Olivier Bachem. “Are Disentangled Representations Helpful for Abstract Visual Reasoning?” In Advances in Neural Information Processing Systems, Vol. 32, 2019.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14197 |
Locatello, Francesco, Gabriele Abbati, Tom Rainforth, Stefan Bauer, Bernhard Schölkopf, and Olivier Bachem. “On the Fairness of Disentangled Representations.” In Advances in Neural Information Processing Systems, 32:14611–14624, 2019.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14200 |
Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, and Olivier Bachem. “Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations.” In Proceedings of the 36th International Conference on Machine Learning, 97:4114–24. ML Research Press, 2019.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14198 |
Fortuin, Vincent, Matthias Hüser, Francesco Locatello, Heiko Strathmann, and Gunnar Rätsch. “SOM-VAE: Interpretable Discrete Representation Learning on Time Series.” In International Conference on Learning Representations, 2018.
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