Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2019. Challenging common assumptions in the unsupervised learning of disentangled representations. Proceedings of the 36th International Conference on Machine Learning. International Conference on Machine Learning vol. 97, 4114–4124.

Gondal MW, Wüthrich M, Miladinovi , Locatello F, Breidt M, Volchkov V, Akpo J, Bachem O, Schölkopf B, Bauer S. 2019. On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32.

Locatello F, Dresdner G, Khanna R, Valera I, Rätsch G. 2018. Boosting black box variational inference. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 31.

Locatello F, Khanna R, Ghosh J, Rätsch G. 2018. Boosting variational inference: An optimization perspective. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics, PMLR, vol. 84, 464–472.

Fortuin V, Hüser M, Locatello F, Strathmann H, Rätsch G. 2018. SOM-VAE: Interpretable discrete representation learning on time series. International Conference on Learning Representations. ICLR: International Conference on Learning Representations.

Yurtsever A, Fercoq O, Locatello F, Cevher V. 2018. A conditional gradient framework for composite convex minimization with applications to semidefinite programming. Proceedings of the 35th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 80, 5727–5736.

Locatello F, Raj A, Karimireddy SP, Rätsch G, Schölkopf B, Stich SU, Jaggi M. 2018. On matching pursuit and coordinate descent. Proceedings of the 35th International Conference on Machine Learning. , PMLR, vol. 80, 3198–3207.

Locatello F, Vincent D, Tolstikhin I, Ratsch G, Gelly S, Scholkopf B. 2018. Clustering meets implicit generative models. 6th International Conference on Learning Representations. International Conference on Machine Learning.

Locatello F, Vincent D, Tolstikhin I, Rätsch G, Gelly S, Schölkopf B. Competitive training of mixtures of independent deep generative models. arXiv, 1804.11130.

Locatello F, Tschannen M, Rätsch G, Jaggi M. 2017. Greedy algorithms for cone constrained optimization with convergence guarantees. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.

Locatello F, Khanna R, Tschannen M, Jaggi M. 2017. A unified optimization view on generalized matching pursuit and Frank-Wolfe. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics vol. 54, 860–868.