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5046 Publications

2019 | Conference Paper | IST-REx-ID: 14189 | OA
The incomplete Rosetta Stone problem: Identifiability results for multi-view nonlinear ICA
L. Gresele, P.K. Rubenstein, A. Mehrjou, F. Locatello, B. Schölkopf, in:, Proceedings of the 35th Conference on Uncertainty in Artificial  Intelligence, ML Research Press, 2019, pp. 217–227.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 14197 | OA
On the fairness of disentangled representations
F. Locatello, G. Abbati, T. Rainforth, S. Bauer, B. Schölkopf, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019, pp. 14611–14624.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 14191 | OA
Stochastic Frank-Wolfe for composite convex minimization
F. Locatello, A. Yurtsever, O. Fercoq, V. Cevher, in:, Advances in Neural Information Processing Systems, 2019, pp. 14291–14301.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 14193 | OA
Are disentangled representations helpful for abstract visual reasoning?
S. van Steenkiste, F. Locatello, J. Schmidhuber, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2019 | Conference Paper | IST-REx-ID: 14200 | OA
Challenging common assumptions in the unsupervised learning of disentangled representations
F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, in:, Proceedings of the 36th International Conference on Machine Learning, ML Research Press, 2019, pp. 4114–4124.
[Preprint] View | Download Preprint (ext.) | arXiv
 

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