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71 Publications


2023 | Preprint | IST-REx-ID: 14963 | OA
Object-centric multiple object tracking
Z. Zhao, J. Wang, M. Horn, Y. Ding, T. He, Z. Bai, D. Zietlow, C.-J.S.-G. Carl-Johann Simon-Gabriel, B. Shuai, Z. Tu, T. Brox, B. Schiele, Y. Fu, F. Locatello, Z. Zhang, T. Xiao, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14961 | OA
Shortcuts for causal discovery of nonlinear models by score matching
F. Montagna, N. Noceti, L. Rosasco, F. Locatello, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14962 | OA
Unsupervised open-vocabulary object localization in videos
K. Fan, Z. Bai, T. Xiao, D. Zietlow, M. Horn, Z. Zhao, C.-J.S.-G. Carl-Johann Simon-Gabriel, M.Z. Shou, F. Locatello, B. Schiele, T. Brox, Z. Zhang, Y. Fu, T. He, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14958 | OA
A sparsity principle for partially observable causal representation learning
D. Xu, D. Yao, S. Lachapelle, P. Taslakian, J. von Kügelgen, F. Locatello, S. Magliacane, in:, Causal Representation Learning Workshop at NeurIPS 2023, OpenReview, 2023.
[Published Version] View | Files available | Download Published Version (ext.)
 

2023 | Conference Paper | IST-REx-ID: 14974 | OA
Causality in the time of LLMs: Round table discussion results of CLeaR 2023
C. Zhang, D. Janzing, M. van der Schaar, F. Locatello, P. Spirtes, K. Zhang, B. Schölkopf, C. Uhler, in:, 2nd Conference on Causal Learning and Reasoning, 2023.
[Submitted Version] View | Files available
 

2022 | Conference Paper | IST-REx-ID: 14173 | OA
Assaying out-of-distribution generalization in transfer learning
F. Wenzel, A. Dittadi, P.V. Gehler, C.-J.S.-G. Carl-Johann Simon-Gabriel, M. Horn, D. Zietlow, D. Kernert, C. Russell, T. Brox, B. Schiele, B. Schölkopf, F. Locatello, in:, 36th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2022, pp. 7181–7198.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14106 | OA
Are two heads the same as one? Identifying disparate treatment in fair neural networks
M. Lohaus, M. Kleindessner, K. Kenthapadi, F. Locatello, C. Russell, in:, 36th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2022, pp. 16548–16562.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14093 | OA
Faster one-sample stochastic conditional gradient method for composite convex minimization
G. Dresdner, M.-L. Vladarean, G. Rätsch, F. Locatello, V. Cevher, A. Yurtsever, in:, Proceedings of the 25th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2022, pp. 8439–8457.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14114 | OA
Leveling down in computer vision: Pareto inefficiencies in fair deep classifiers
D. Zietlow, M. Lohaus, G. Balakrishnan, M. Kleindessner, F. Locatello, B. Scholkopf, C. Russell, in:, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition, Institute of Electrical and Electronics Engineers, 2022, pp. 10400–10411.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2022 | Conference Paper | IST-REx-ID: 14168 | OA
Neural attentive circuits
N. Rahaman, M. Weiss, F. Locatello, C. Pal, Y. Bengio, B. Schölkopf, L.E. Li, N. Ballas, in:, 36th Conference on Neural Information Processing Systems, 2022.
[Preprint] View | Download Preprint (ext.) | arXiv
 

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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