Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
5046 Publications
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.
[Preprint]
View
| Download Preprint (ext.)
| 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.
[Preprint]
View
| Download Preprint (ext.)
| 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.
[Preprint]
View
| Download Preprint (ext.)
| 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.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2019 | Conference Paper | IST-REx-ID: 14200 |
Locatello F, Bauer S, Lucic M, et al. Challenging common assumptions in the unsupervised learning of disentangled representations. In: Proceedings of the 36th International Conference on Machine Learning. Vol 97. ML Research Press; 2019:4114-4124.
[Preprint]
View
| Download Preprint (ext.)
| arXiv