Please note that ISTA Research Explorer no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
71 Publications
2024 | Conference Paper | IST-REx-ID: 14213 | 
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
D. Lao, Z. Hu, F. Locatello, Y. Yang, S. Soatto, in:, 1st Conference on Parsimony and Learning, 2024.
2023 | Conference Paper | IST-REx-ID: 14105 |
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
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.
2023 | Conference Paper | IST-REx-ID: 14208 |
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
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.
2023 | Preprint | IST-REx-ID: 14209 |
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
M.F. Burg, F. Wenzel, D. Zietlow, M. Horn, O. Makansi, F. Locatello, C. Russell, ArXiv (n.d.).
2023 | Conference Paper | IST-REx-ID: 14211 |
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
F. Montagna, N. Noceti, L. Rosasco, K. Zhang, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.
2023 | Conference Paper | IST-REx-ID: 14212 |
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
F. Montagna, N. Noceti, L. Rosasco, K. Zhang, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.
2023 | Conference Paper | IST-REx-ID: 14214 |
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
Y. Liu, A. Alahi, C. Russell, M. Horn, D. Zietlow, B. Schölkopf, F. Locatello, in:, 2nd Conference on Causal Learning and Reasoning, 2023.
2023 | Conference Paper | IST-REx-ID: 14217 |
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
L. Moschella, V. Maiorca, M. Fumero, A. Norelli, F. Locatello, E. Rodolà, in:, The 11th International Conference on Learning Representations, 2023.
2023 | Conference Paper | IST-REx-ID: 14222 |
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
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.
2023 | Conference Paper | IST-REx-ID: 14218 |
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
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.
2023 | Conference Paper | IST-REx-ID: 14219 |
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
A. Zadaianchuk, M. Kleindessner, Y. Zhu, F. Locatello, T. Brox, in:, The 11th International Conference on Learning Representations, 2023.
2023 | Preprint | IST-REx-ID: 14333 |
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
P.M. Faller, L.C. Vankadara, A.A. Mastakouri, F. Locatello, D. Janzing, ArXiv (n.d.).
2023 | Journal Article | IST-REx-ID: 14949 |
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.)
M. Burg, F. Wenzel, D. Zietlow, M. Horn, O. Makansi, F. Locatello, C. Russell, Journal of Machine Learning Research (2023).
2023 | Preprint | IST-REx-ID: 14946 |
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
D. Yao, D. Xu, S. Lachapelle, S. Magliacane, P. Taslakian, G. Martius, J. von Kügelgen, F. Locatello, ArXiv (n.d.).
2023 | Preprint | IST-REx-ID: 14952 |
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
V. Maiorca, L. Moschella, A. Norelli, M. Fumero, F. Locatello, E. Rodolà, ArXiv (n.d.).
2023 | Preprint | IST-REx-ID: 14948 |
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
A. Kori, F. Locatello, F.D.S. Ribeiro, F. Toni, B. Glocker, ArXiv (n.d.).
2023 | Preprint | IST-REx-ID: 14953 |
Sample complexity bounds for score-matching: Causal discovery and generative modeling
Z. Zhu, F. Locatello, V. Cevher, ArXiv (n.d.).
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
Z. Zhu, F. Locatello, V. Cevher, ArXiv (n.d.).
2023 | Preprint | IST-REx-ID: 14954 |
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
F. Montagna, A.A. Mastakouri, E. Eulig, N. Noceti, L. Rosasco, D. Janzing, B. Aragam, F. Locatello, ArXiv (n.d.).
2023 | Preprint | IST-REx-ID: 14210 |
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
M. Fumero, F. Wenzel, L. Zancato, A. Achille, E. Rodolà, S. Soatto, B. Schölkopf, F. Locatello, ArXiv (n.d.).
2023 | Preprint | IST-REx-ID: 14207 |
Rotating features for object discovery
S. Löwe, P. Lippe, F. Locatello, M. Welling, ArXiv (n.d.).
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
S. Löwe, P. Lippe, F. Locatello, M. Welling, ArXiv (n.d.).
2023 | Preprint | IST-REx-ID: 14963 |
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
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.).
2023 | Preprint | IST-REx-ID: 14961 |
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
F. Montagna, N. Noceti, L. Rosasco, F. Locatello, ArXiv (n.d.).
2023 | Preprint | IST-REx-ID: 14962 |
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
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.).
2023 | Conference Paper | IST-REx-ID: 14958 |
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.)
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.
2023 | Conference Paper | IST-REx-ID: 14974 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14173 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14106 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14093 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14114 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14168 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14170 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14172 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14107 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14171 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14174 |
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
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.
2022 | Conference Paper | IST-REx-ID: 14175 |
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
O. Makansi, J. von Kügelgen, F. Locatello, P. Gehler, D. Janzing, T. Brox, B. Schölkopf, in:, 10th International Conference on Learning Representations, 2022.
2022 | Preprint | IST-REx-ID: 14220 |
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
D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, F. Locatello, ArXiv (n.d.).
2022 | Conference Paper | IST-REx-ID: 14215 |
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
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.
2022 | Preprint | IST-REx-ID: 14216 |
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
A. Norelli, M. Fumero, V. Maiorca, L. Moschella, E. Rodolà, F. Locatello, ArXiv (n.d.).
2021 | Conference Paper | IST-REx-ID: 14177 |
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
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.
2021 | Conference Paper | IST-REx-ID: 14176 |
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
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.
2021 | Conference Paper | IST-REx-ID: 14182 |
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
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.
2021 | Conference Paper | IST-REx-ID: 14181 |
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
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.
2021 | Conference Paper | IST-REx-ID: 14179 |
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
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.
2021 | Conference Paper | IST-REx-ID: 14180 |
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
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.
2021 | Journal Article | IST-REx-ID: 14117 |
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
B. Scholkopf, F. Locatello, S. Bauer, N.R. Ke, N. Kalchbrenner, A. Goyal, Y. Bengio, Proceedings of the IEEE 109 (2021) 612–634.
2021 | Conference Paper | IST-REx-ID: 14178 |
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
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.
2021 | Preprint | IST-REx-ID: 14221 |
Enforcing and discovering structure in machine learning
F. Locatello, ArXiv (n.d.).
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
F. Locatello, ArXiv (n.d.).
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
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.
2020 | Journal Article | IST-REx-ID: 14125 |
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
Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired feature sets. Bioinformatics. 36(Supplement_2), i919–i927.
2020 | Conference Paper | IST-REx-ID: 14186 |
A commentary on the unsupervised learning of disentangled representations
F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, in:, The 34th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2020, pp. 13681–13684.
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, in:, The 34th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2020, pp. 13681–13684.
2020 | Conference Paper | IST-REx-ID: 14188 |
Weakly-supervised disentanglement without compromises
F. Locatello, B. Poole, G. Rätsch, B. Schölkopf, O. Bachem, M. Tschannen, in:, Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 6348–6359.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, B. Poole, G. Rätsch, B. Schölkopf, O. Bachem, M. Tschannen, in:, Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 6348–6359.
2020 | Conference Paper | IST-REx-ID: 14187 |
Stochastic Frank-Wolfe for constrained finite-sum minimization
G. Négiar, G. Dresdner, A. Tsai, L.E. Ghaoui, F. Locatello, R.M. Freund, F. Pedregosa, in:, Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 7253–7262.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
G. Négiar, G. Dresdner, A. Tsai, L.E. Ghaoui, F. Locatello, R.M. Freund, F. Pedregosa, in:, Proceedings of the 37th International Conference on Machine Learning, 2020, pp. 7253–7262.
2020 | Journal Article | IST-REx-ID: 14195 |
A sober look at the unsupervised learning of disentangled representations and their evaluation
F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, Journal of Machine Learning Research 21 (2020).
[Published Version]
View
| Download Published Version (ext.)
| arXiv
F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, Journal of Machine Learning Research 21 (2020).
2020 | Conference Paper | IST-REx-ID: 14326 |
Object-centric learning with slot attention
F. Locatello, D. Weissenborn, T. Unterthiner, A. Mahendran, G. Heigold, J. Uszkoreit, A. Dosovitskiy, T. Kipf, in:, Advances in Neural Information Processing Systems, Curran Associates, 2020, pp. 11525–11538.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, D. Weissenborn, T. Unterthiner, A. Mahendran, G. Heigold, J. Uszkoreit, A. Dosovitskiy, T. Kipf, in:, Advances in Neural Information Processing Systems, Curran Associates, 2020, pp. 11525–11538.
2019 | Conference Paper | IST-REx-ID: 14184 |
Disentangling factors of variation using few labels
F. Locatello, M. Tschannen, S. Bauer, G. Rätsch, B. Schölkopf, O. Bachem, in:, 8th International Conference on Learning Representations, 2019.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, M. Tschannen, S. Bauer, G. Rätsch, B. Schölkopf, O. Bachem, in:, 8th International Conference on Learning Representations, 2019.
2019 | Conference Paper | IST-REx-ID: 14189 |
The incomplete Rosetta Stone problem: Identifiability results for multi-view nonlinear ICA
L. Gresele, P.K. Rubenstein, A. Mehrjou, F. Locatello, B. Schölkopf, in:, Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence, ML Research Press, 2019, pp. 217–227.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
L. Gresele, P.K. Rubenstein, A. Mehrjou, F. Locatello, B. Schölkopf, in:, Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence, ML Research Press, 2019, pp. 217–227.
2019 | Conference Paper | IST-REx-ID: 14197 |
On the fairness of disentangled representations
F. Locatello, G. Abbati, T. Rainforth, S. Bauer, B. Schölkopf, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019, pp. 14611–14624.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, G. Abbati, T. Rainforth, S. Bauer, B. Schölkopf, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019, pp. 14611–14624.
2019 | Conference Paper | IST-REx-ID: 14191 |
Stochastic Frank-Wolfe for composite convex minimization
F. Locatello, A. Yurtsever, O. Fercoq, V. Cevher, in:, Advances in Neural Information Processing Systems, 2019, pp. 14291–14301.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, A. Yurtsever, O. Fercoq, V. Cevher, in:, Advances in Neural Information Processing Systems, 2019, pp. 14291–14301.
2019 | Conference Paper | IST-REx-ID: 14193 |
Are disentangled representations helpful for abstract visual reasoning?
S. van Steenkiste, F. Locatello, J. Schmidhuber, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
S. van Steenkiste, F. Locatello, J. Schmidhuber, O. Bachem, in:, Advances in Neural Information Processing Systems, 2019.
2019 | Conference Paper | IST-REx-ID: 14200 |
Challenging common assumptions in the unsupervised learning of disentangled representations
F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, in:, Proceedings of the 36th International Conference on Machine Learning, ML Research Press, 2019, pp. 4114–4124.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem, in:, Proceedings of the 36th International Conference on Machine Learning, ML Research Press, 2019, pp. 4114–4124.
2019 | Conference Paper | IST-REx-ID: 14190 |
On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset
M.W. Gondal, M. Wüthrich, Đ. Miladinović, F. Locatello, M. Breidt, V. Volchkov, J. Akpo, O. Bachem, B. Schölkopf, S. Bauer, in:, Advances in Neural Information Processing Systems, 2019.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
M.W. Gondal, M. Wüthrich, Đ. Miladinović, F. Locatello, M. Breidt, V. Volchkov, J. Akpo, O. Bachem, B. Schölkopf, S. Bauer, in:, Advances in Neural Information Processing Systems, 2019.
2018 | Conference Paper | IST-REx-ID: 14202 |
Boosting black box variational inference
F. Locatello, G. Dresdner, R. Khanna, I. Valera, G. Rätsch, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2018.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, G. Dresdner, R. Khanna, I. Valera, G. Rätsch, in:, Advances in Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2018.
2018 | Conference Paper | IST-REx-ID: 14201 |
Boosting variational inference: An optimization perspective
F. Locatello, R. Khanna, J. Ghosh, G. Rätsch, in:, Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, ML Research Press, 2018, pp. 464–472.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, R. Khanna, J. Ghosh, G. Rätsch, in:, Proceedings of the 21st International Conference on Artificial Intelligence and Statistics, ML Research Press, 2018, pp. 464–472.
2018 | Conference Paper | IST-REx-ID: 14198 |
SOM-VAE: Interpretable discrete representation learning on time series
V. Fortuin, M. Hüser, F. Locatello, H. Strathmann, G. Rätsch, in:, International Conference on Learning Representations, 2018.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
V. Fortuin, M. Hüser, F. Locatello, H. Strathmann, G. Rätsch, in:, International Conference on Learning Representations, 2018.
2018 | Conference Paper | IST-REx-ID: 14203 |
A conditional gradient framework for composite convex minimization with applications to semidefinite programming
A. Yurtsever, O. Fercoq, F. Locatello, V. Cevher, in:, Proceedings of the 35th International Conference on Machine Learning, ML Research Press, 2018, pp. 5727–5736.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
A. Yurtsever, O. Fercoq, F. Locatello, V. Cevher, in:, Proceedings of the 35th International Conference on Machine Learning, ML Research Press, 2018, pp. 5727–5736.
2018 | Conference Paper | IST-REx-ID: 14204 |
On matching pursuit and coordinate descent
F. Locatello, A. Raj, S.P. Karimireddy, G. Rätsch, B. Schölkopf, S.U. Stich, M. Jaggi, in:, Proceedings of the 35th International Conference on Machine Learning, ML Research Press, 2018, pp. 3198–3207.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, A. Raj, S.P. Karimireddy, G. Rätsch, B. Schölkopf, S.U. Stich, M. Jaggi, in:, Proceedings of the 35th International Conference on Machine Learning, ML Research Press, 2018, pp. 3198–3207.
2018 | Conference Paper | IST-REx-ID: 14224 |
Clustering meets implicit generative models
F. Locatello, D. Vincent, I. Tolstikhin, G. Ratsch, S. Gelly, B. Scholkopf, in:, 6th International Conference on Learning Representations, 2018.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, D. Vincent, I. Tolstikhin, G. Ratsch, S. Gelly, B. Scholkopf, in:, 6th International Conference on Learning Representations, 2018.
2018 | Preprint | IST-REx-ID: 14327 |
Competitive training of mixtures of independent deep generative models
F. Locatello, D. Vincent, I. Tolstikhin, G. Rätsch, S. Gelly, B. Schölkopf, ArXiv (n.d.).
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
F. Locatello, D. Vincent, I. Tolstikhin, G. Rätsch, S. Gelly, B. Schölkopf, ArXiv (n.d.).
2017 | Conference Paper | IST-REx-ID: 14206 |
Greedy algorithms for cone constrained optimization with convergence guarantees
F. Locatello, M. Tschannen, G. Rätsch, M. Jaggi, in:, Advances in Neural Information Processing Systems, 2017.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, M. Tschannen, G. Rätsch, M. Jaggi, in:, Advances in Neural Information Processing Systems, 2017.
2017 | Conference Paper | IST-REx-ID: 14205 |
A unified optimization view on generalized matching pursuit and Frank-Wolfe
F. Locatello, R. Khanna, M. Tschannen, M. Jaggi, in:, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2017, pp. 860–868.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
F. Locatello, R. Khanna, M. Tschannen, M. Jaggi, in:, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, ML Research Press, 2017, pp. 860–868.