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87 Publications
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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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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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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14201 |
Locatello, Francesco, Rajiv Khanna, Joydeep Ghosh, and Gunnar Rätsch. “Boosting Variational Inference: An Optimization Perspective.” In Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, 84:464–72. ML Research Press, 2018.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14202 |
Locatello, Francesco, Gideon Dresdner, Rajiv Khanna, Isabel Valera, and Gunnar Rätsch. “Boosting Black Box Variational Inference.” In Advances in Neural Information Processing Systems, Vol. 31. Neural Information Processing Systems Foundation, 2018.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14203 |
Yurtsever, Alp, Olivier Fercoq, Francesco Locatello, and Volkan Cevher. “A Conditional Gradient Framework for Composite Convex Minimization with Applications to Semidefinite Programming.” In Proceedings of the 35th International Conference on Machine Learning, 80:5727–36. ML Research Press, 2018.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14204 |
Locatello, Francesco, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rätsch, Bernhard Schölkopf, Sebastian U. Stich, and Martin Jaggi. “On Matching Pursuit and Coordinate Descent.” In Proceedings of the 35th International Conference on Machine Learning, 80:3198–3207. ML Research Press, 2018.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14224 |
Locatello, Francesco, Damien Vincent, Ilya Tolstikhin, Gunnar Ratsch, Sylvain Gelly, and Bernhard Scholkopf. “Clustering Meets Implicit Generative Models.” In 6th International Conference on Learning Representations, 2018.
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| arXiv
2018 | Submitted | Preprint | IST-REx-ID: 14327 |
Locatello, Francesco, Damien Vincent, Ilya Tolstikhin, Gunnar Rätsch, Sylvain Gelly, and Bernhard Schölkopf. “Competitive Training of Mixtures of Independent Deep Generative Models.” ArXiv, n.d. https://doi.org/10.48550/arXiv.1804.11130.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 14205 |
Locatello, Francesco, Rajiv Khanna, Michael Tschannen, and Martin Jaggi. “A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe.” In Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 54:860–68. ML Research Press, 2017.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 14206 |
Locatello, Francesco, Michael Tschannen, Gunnar Rätsch, and Martin Jaggi. “Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees.” In Advances in Neural Information Processing Systems, 2017.
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| arXiv
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