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.

Gondal, Muhammad Waleed, Manuel Wüthrich, ore Miladinovi, 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.

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.

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.

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.

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.

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.

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.

Locatello, Francesco, Damien Vincent, Ilya Tolstikhin, Gunnar Rätsch, Sylvain Gelly, and Bernhard Schölkopf. “Competitive Training of Mixtures of Independent Deep Generative Models.”https://doi.org/10.48550/arXiv.1804.11130__ArXiv, n.d.https://doi.org/10.48550/arXiv.1804.11130 .

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.

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.