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Francesco Locatello

Empirical Inference Alumni

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Empirical Inference Conference Paper Representation Learning for Out-of-distribution Generalization in Reinforcement Learning Learning Träuble*, F., Dittadi*, A., Wüthrich, M., Widmaier, F., Gehler, P., Winther, O., Locatello, F., Bachem, O., Schölkopf, B., Bauer, S. ICML 2021 Workshop on Unsupervised Reinforcement Learning (ICML 2021) , ICML 2021 Workshop on Unsupervised Reinforcement Learning (ICML 2021) , July 2021, *equal contribution (Published) URL BibTeX
Empirical Inference Conference Paper On the Transfer of Disentangled Representations in Realistic Settings Dittadi*, A., Träuble*, F., Locatello, F., Wüthrich, M., Agrawal, V., Winther, O., Bauer, S., Schölkopf, B. In The Ninth International Conference on Learning Representations (ICLR), The 9th International Conference on Learning Representations (ICLR 2021) , May 2021, *equal contribution (Published) URL BibTeX
Empirical Inference Article Toward Causal Representation Learning Schölkopf*, B., Locatello*, F., Bauer, S., Ke, N. R., Kalchbrenner, N., Goyal, A., Bengio, Y. Proceedings of the IEEE, 109(5):612-634, 2021, *equal contribution (Published) DOI URL BibTeX
Empirical Inference Conference Paper Object-Centric Learning with Slot Attention Locatello, F., Weissenborn, D., Unterthiner, T., Mahendran, A., Heigold, G., Uszkoreit, J., Dosovitskiy, A., Kipf, T. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 11525-11538, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX
Empirical Inference Ph.D. Thesis Enforcing and Discovering Structure in Machine Learning Locatello, F. ETH Zurich, Switzerland, November 2020, (CLS Fellowship Program) (Published) BibTeX
Empirical Inference Conference Paper Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization Negiar, G., Dresdner, G., Tsai, A. Y., El Ghaoui, L., Locatello, F., Freund, R. M., Pedregosa, F. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:7253-7262, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020 (Published) URL BibTeX
Empirical Inference Conference Paper Weakly-Supervised Disentanglement Without Compromises Locatello, F., Poole, B., Rätsch, G., Schölkopf, B., Bachem, O., Tschannen, M. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:6348-6359, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020 (Published) URL BibTeX
Empirical Inference Conference Paper Disentangling Factors of Variations Using Few Labels Locatello, F., Tschannen, M., Bauer, S., Rätsch, G., Schölkopf, B., Bachem, O. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) arXiv URL BibTeX
Empirical Inference Conference Paper A Commentary on the Unsupervised Learning of Disentangled Representations Locatello, F., Bauer, S., Lucic, M., Rätsch, G., Gelly, S., Schölkopf, B., Bachem, O. Proceedings of the 34th Conference on Artificial Intelligence (AAAI), 34(9):13681-13684, AAAI Press, February 2020, Sister Conference Track (Published) DOI URL BibTeX
Empirical Inference Article A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation Locatello, F., Bauer, S., Lucic, M., Raetsch, G., Gelly, S., Schölkopf, B., Bachem, O. Journal of Machine Learning Research, 21:1-62, 2020 (Published) URL BibTeX
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Empirical Inference Conference Paper Representation Learning for Out-of-distribution Generalization in Reinforcement Learning Learning Träuble*, F., Dittadi*, A., Wüthrich, M., Widmaier, F., Gehler, P., Winther, O., Locatello, F., Bachem, O., Schölkopf, B., Bauer, S. ICML 2021 Workshop on Unsupervised Reinforcement Learning (ICML 2021) , ICML 2021 Workshop on Unsupervised Reinforcement Learning (ICML 2021) , July 2021, *equal contribution (Published) URL BibTeX
Empirical Inference Conference Paper On the Transfer of Disentangled Representations in Realistic Settings Dittadi*, A., Träuble*, F., Locatello, F., Wüthrich, M., Agrawal, V., Winther, O., Bauer, S., Schölkopf, B. In The Ninth International Conference on Learning Representations (ICLR), The 9th International Conference on Learning Representations (ICLR 2021) , May 2021, *equal contribution (Published) URL BibTeX
Empirical Inference Article Toward Causal Representation Learning Schölkopf*, B., Locatello*, F., Bauer, S., Ke, N. R., Kalchbrenner, N., Goyal, A., Bengio, Y. Proceedings of the IEEE, 109(5):612-634, 2021, *equal contribution (Published) DOI URL BibTeX
Empirical Inference Conference Paper Object-Centric Learning with Slot Attention Locatello, F., Weissenborn, D., Unterthiner, T., Mahendran, A., Heigold, G., Uszkoreit, J., Dosovitskiy, A., Kipf, T. Advances in Neural Information Processing Systems 33 (NeurIPS 2020), 11525-11538, (Editors: H. Larochelle and M. Ranzato and R. Hadsell and M. F. Balcan and H. Lin), Curran Associates, Inc., 34th Annual Conference on Neural Information Processing Systems, December 2020 (Published) URL BibTeX
Empirical Inference Ph.D. Thesis Enforcing and Discovering Structure in Machine Learning Locatello, F. ETH Zurich, Switzerland, November 2020, (CLS Fellowship Program) (Published) BibTeX
Empirical Inference Conference Paper Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization Negiar, G., Dresdner, G., Tsai, A. Y., El Ghaoui, L., Locatello, F., Freund, R. M., Pedregosa, F. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:7253-7262, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020 (Published) URL BibTeX
Empirical Inference Conference Paper Weakly-Supervised Disentanglement Without Compromises Locatello, F., Poole, B., Rätsch, G., Schölkopf, B., Bachem, O., Tschannen, M. Proceedings of the 37th International Conference on Machine Learning (ICML), 119:6348-6359, Proceedings of Machine Learning Research, (Editors: Hal Daumé III and Aarti Singh), PMLR, July 2020 (Published) URL BibTeX
Empirical Inference Conference Paper Disentangling Factors of Variations Using Few Labels Locatello, F., Tschannen, M., Bauer, S., Rätsch, G., Schölkopf, B., Bachem, O. 8th International Conference on Learning Representations (ICLR), April 2020 (Published) arXiv URL BibTeX
Empirical Inference Conference Paper A Commentary on the Unsupervised Learning of Disentangled Representations Locatello, F., Bauer, S., Lucic, M., Rätsch, G., Gelly, S., Schölkopf, B., Bachem, O. Proceedings of the 34th Conference on Artificial Intelligence (AAAI), 34(9):13681-13684, AAAI Press, February 2020, Sister Conference Track (Published) DOI URL BibTeX
Empirical Inference Article A Sober Look at the Unsupervised Learning of Disentangled Representations and their Evaluation Locatello, F., Bauer, S., Lucic, M., Raetsch, G., Gelly, S., Schölkopf, B., Bachem, O. Journal of Machine Learning Research, 21:1-62, 2020 (Published) URL BibTeX
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