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5767 Publications


2019 | Conference Paper | IST-REx-ID: 14189 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2019 | Conference Paper | IST-REx-ID: 14197 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2019 | Conference Paper | IST-REx-ID: 14191 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2019 | Conference Paper | IST-REx-ID: 14193 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2019 | Conference Paper | IST-REx-ID: 14200 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 

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