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71 Publications


2022 | Conference Paper | IST-REx-ID: 14170 | OA
Generalization and robustness implications in object-centric learning
A. Dittadi, S. Papa, M.D. Vita, B. Schölkopf, O. Winther, F. Locatello, in:, Proceedings of the 39th International Conference on Machine Learning, ML Research Press, n.d., pp. 5221–5285.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14172 | OA
Visual representation learning does not generalize strongly within the same domain
L. Schott, J. von Kügelgen, F. Träuble, P. Gehler, C. Russell, M. Bethge, B. Schölkopf, F. Locatello, W. Brendel, in:, 10th International Conference on Learning Representations, 2022.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14107 | OA
Self-supervised amodal video object segmentation
J. Yao, Y. Hong, C. Wang, T. Xiao, T. He, F. Locatello, D. Wipf, Y. Fu, Z. Zhang, in:, 36th Conference on Neural Information Processing Systems, 2022.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14171 | OA
Score matching enables causal discovery of nonlinear additive noise models
P. Rolland, V. Cevher, M. Kleindessner, C. Russel, B. Schölkopf, D. Janzing, F. Locatello, in:, Proceedings of the 39th International Conference on Machine Learning, ML Research Press, 2022, pp. 18741–18753.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14174 | OA
The role of pretrained representations for the OOD generalization of reinforcement learning agents
A. Dittadi, F. Träuble, M. Wüthrich, F. Widmaier, P. Gehler, O. Winther, F. Locatello, O. Bachem, B. Schölkopf, S. Bauer, in:, 10th International Conference on Learning Representations, 2022.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14175 | OA
You mostly walk alone: Analyzing feature attribution in trajectory prediction
O. Makansi, J. von Kügelgen, F. Locatello, P. Gehler, D. Janzing, T. Brox, B. Schölkopf, in:, 10th International Conference on Learning Representations, 2022.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Preprint | IST-REx-ID: 14220 | OA
Compositional multi-object reinforcement learning with linear relation networks
D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, F. Locatello, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14215 | OA
A general purpose neural architecture for geospatial systems
N. Rahaman, M. Weiss, F. Träuble, F. Locatello, A. Lacoste, Y. Bengio, C. Pal, L.E. Li, B. Schölkopf, in:, 36th Conference on Neural Information Processing Systems, n.d.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Preprint | IST-REx-ID: 14216 | OA
ASIF: Coupled data turns unimodal models to multimodal without training
A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, F. Locatello, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 14177 | OA
On disentangled representations learned from correlated data
F. Träuble, E. Creager, N. Kilbertus, F. Locatello, A. Dittadi, A. Goyal, B. Schölkopf, S. Bauer, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 10401–10412.
[Published Version] View | Download Published Version (ext.) | arXiv
 

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