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71 Publications


2024 | Conference Paper | IST-REx-ID: 14213 | OA
Divided attention: Unsupervised multi-object discovery with contextually separated slots
D. Lao, Z. Hu, F. Locatello, Y. Yang, S. Soatto, in:, 1st Conference on Parsimony and Learning, 2024.
[Published Version] View | Files available | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14105 | OA
TeST: Test-time Self-Training under distribution shift
S. Sinha, P. Gehler, F. Locatello, B. Schiele, in:, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision, Institute of Electrical and Electronics Engineers, 2023.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14208 | OA
Benign overfitting in deep neural networks under lazy training
Z. Zhu, F. Liu, G.G. Chrysos, F. Locatello, V. Cevher, in:, Proceedings of the 40th International Conference on Machine Learning, ML Research Press, 2023, pp. 43105–43128.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14209 | OA
A data augmentation perspective on diffusion models and retrieval
M.F. Burg, F. Wenzel, D. Zietlow, M. Horn, O. Makansi, F. Locatello, C. Russell, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14211 | OA
Causal discovery with score matching on additive models with arbitrary noise
F. Montagna, N. Noceti, L. Rosasco, K. Zhang, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14212 | OA
Scalable causal discovery with score matching
F. Montagna, N. Noceti, L. Rosasco, K. Zhang, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14214 | OA
Causal triplet: An open challenge for intervention-centric causal representation learning
Y. Liu, A. Alahi, C. Russell, M. Horn, D. Zietlow, B. Schölkopf, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14217 | OA
Relative representations enable zero-shot latent space communication
L. Moschella, V. Maiorca, M. Fumero, A. Norelli, F. Locatello, E. Rodolà, in:, The 11th International Conference on Learning Representations, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14222 | OA
Unsupervised object learning via common fate
M. Tangemann, S. Schneider, J. von Kügelgen, F. Locatello, P. Gehler, T. Brox, M. Kümmerer, M. Bethge, B. Schölkopf, in:, 2nd Conference on Causal Learning and Reasoning, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14218 | OA
Bridging the gap to real-world object-centric learning
M. Seitzer, M. Horn, A. Zadaianchuk, D. Zietlow, T. Xiao, C.-J.S.-G. Carl-Johann Simon-Gabriel, T. He, Z. Zhang, B. Schölkopf, T. Brox, F. Locatello, in:, The 11th International Conference on Learning Representations, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Conference Paper | IST-REx-ID: 14219 | OA
Unsupervised semantic segmentation with self-supervised object-centric representations
A. Zadaianchuk, M. Kleindessner, Y. Zhu, F. Locatello, T. Brox, in:, The 11th International Conference on Learning Representations, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14333 | OA
Self-compatibility: Evaluating causal discovery without ground truth
P.M. Faller, L.C. Vankadara, A.A. Mastakouri, F. Locatello, D. Janzing, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Journal Article | IST-REx-ID: 14949 | OA
Image retrieval outperforms diffusion models on data augmentation
M. Burg, F. Wenzel, D. Zietlow, M. Horn, O. Makansi, F. Locatello, C. Russell, Journal of Machine Learning Research (2023).
[Published Version] View | Files available | Download Published Version (ext.)
 

2023 | Preprint | IST-REx-ID: 14946 | OA
Multi-view causal representation learning with partial observability
D. Yao, D. Xu, S. Lachapelle, S. Magliacane, P. Taslakian, G. Martius, J. von Kügelgen, F. Locatello, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14952 | OA
Latent space translation via semantic alignment
V. Maiorca, L. Moschella, A. Norelli, M. Fumero, F. Locatello, E. Rodolà, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14948 | OA
Grounded object centric learning
A. Kori, F. Locatello, F.D.S. Ribeiro, F. Toni, B. Glocker, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14953 | OA [Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14954 | OA
Assumption violations in causal discovery and the robustness of score matching
F. Montagna, A.A. Mastakouri, E. Eulig, N. Noceti, L. Rosasco, D. Janzing, B. Aragam, F. Locatello, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14210 | OA
Leveraging sparse and shared feature activations for disentangled representation learning
M. Fumero, F. Wenzel, L. Zancato, A. Achille, E. Rodolà, S. Soatto, B. Schölkopf, F. Locatello, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Preprint | IST-REx-ID: 14207 | OA
Rotating features for object discovery
S. Löwe, P. Lippe, F. Locatello, M. Welling, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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
 

2021 | Conference Paper | IST-REx-ID: 14176 | OA
Neighborhood contrastive learning applied to online patient monitoring
H. Yèche, G. Dresdner, F. Locatello, M. Hüser, G. Rätsch, in:, Proceedings of 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 11964–11974.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 14182 | OA
Backward-compatible prediction updates: A probabilistic approach
F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf, P. Gehler, in:, 35th Conference on Neural Information Processing Systems, 2021, pp. 116–128.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 14181 | OA
Boosting variational inference with locally adaptive step-sizes
G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, G. Rätsch, in:, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, 2021, pp. 2337–2343.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 14179 | OA
Self-supervised learning with data augmentations provably isolates content from style
J. von Kügelgen, Y. Sharma, L. Gresele, W. Brendel, B. Schölkopf, M. Besserve, F. Locatello, in:, Advances in Neural Information Processing Systems, 2021, pp. 16451–16467.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 14180 | OA
Dynamic inference with neural interpreters
N. Rahaman, M.W. Gondal, S. Joshi, P. Gehler, Y. Bengio, F. Locatello, B. Schölkopf, in:, Advances in Neural Information Processing Systems, 2021, pp. 10985–10998.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Journal Article | IST-REx-ID: 14117 | OA
Toward causal representation learning
B. Scholkopf, F. Locatello, S. Bauer, N.R. Ke, N. Kalchbrenner, A. Goyal, Y. Bengio, Proceedings of the IEEE 109 (2021) 612–634.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 14178 | OA
On the transfer of disentangled representations in realistic settings
A. Dittadi, F. Träuble, F. Locatello, M. Wüthrich, V. Agrawal, O. Winther, S. Bauer, B. Schölkopf, in:, The Ninth International Conference on Learning Representations, 2021.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2021 | Preprint | IST-REx-ID: 14221 | OA [Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2021 | Conference Paper | IST-REx-ID: 14332
Representation learning for out-of-distribution generalization in reinforcement learning
F. Träuble, A. Dittadi, M. Wuthrich, F. Widmaier, P.V. Gehler, O. Winther, F. Locatello, O. Bachem, B. Schölkopf, S. Bauer, in:, ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021.
View
 

2020 | Journal Article | IST-REx-ID: 14125 | OA
SCIM: Universal single-cell matching with unpaired feature sets
Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired feature sets. Bioinformatics. 36(Supplement_2), i919–i927.
[Published Version] View | Files available | DOI | Download Published Version (ext.) | PubMed | Europe PMC
 

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