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71 Publications
2023 | Preprint | IST-REx-ID: 14963 | 
Zhao, Z., Wang, J., Horn, M., Ding, Y., He, T., Bai, Z., … Xiao, T. (n.d.). Object-centric multiple object tracking. arXiv. https://doi.org/10.48550/arXiv.2309.00233
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2023 | Preprint | IST-REx-ID: 14961 |
Montagna, F., Noceti, N., Rosasco, L., & Locatello, F. (n.d.). Shortcuts for causal discovery of nonlinear models by score matching. arXiv. https://doi.org/10.48550/arXiv.2310.14246
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2023 | Preprint | IST-REx-ID: 14962 |
Fan, K., Bai, Z., Xiao, T., Zietlow, D., Horn, M., Zhao, Z., … He, T. (n.d.). Unsupervised open-vocabulary object localization in videos. arXiv. https://doi.org/10.48550/arXiv.2309.09858
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2023 | Conference Paper | IST-REx-ID: 14958 |
Xu, D., Yao, D., Lachapelle, S., Taslakian, P., von Kügelgen, J., Locatello, F., & Magliacane, S. (2023). A sparsity principle for partially observable causal representation learning. In Causal Representation Learning Workshop at NeurIPS 2023. New Orleans, LA, United States: OpenReview.
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2023 | Conference Paper | IST-REx-ID: 14974 |
Zhang, C., Janzing, D., van der Schaar, M., Locatello, F., Spirtes, P., Zhang, K., … Uhler, C. (2023). Causality in the time of LLMs: Round table discussion results of CLeaR 2023. In 2nd Conference on Causal Learning and Reasoning. Tübingen, Germany.
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2022 | Conference Paper | IST-REx-ID: 14173 |
Wenzel, F., Dittadi, A., Gehler, P. V., Carl-Johann Simon-Gabriel, C.-J. S.-G., Horn, M., Zietlow, D., … Locatello, F. (2022). Assaying out-of-distribution generalization in transfer learning. In 36th Conference on Neural Information Processing Systems (Vol. 35, pp. 7181–7198). New Orleans, LA, United States: Neural Information Processing Systems Foundation.
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2022 | Conference Paper | IST-REx-ID: 14106 |
Lohaus, M., Kleindessner, M., Kenthapadi, K., Locatello, F., & Russell, C. (2022). Are two heads the same as one? Identifying disparate treatment in fair neural networks. In 36th Conference on Neural Information Processing Systems (Vol. 35, pp. 16548–16562). New Orleans, LA, United States: Neural Information Processing Systems Foundation.
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2022 | Conference Paper | IST-REx-ID: 14093 |
Dresdner, G., Vladarean, M.-L., Rätsch, G., Locatello, F., Cevher, V., & Yurtsever, A. (2022). Faster one-sample stochastic conditional gradient method for composite convex minimization. In Proceedings of the 25th International Conference on Artificial Intelligence and Statistics (Vol. 151, pp. 8439–8457). Virtual: ML Research Press.
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2022 | Conference Paper | IST-REx-ID: 14114 |
Zietlow, D., Lohaus, M., Balakrishnan, G., Kleindessner, M., Locatello, F., Scholkopf, B., & Russell, C. (2022). Leveling down in computer vision: Pareto inefficiencies in fair deep classifiers. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 10400–10411). New Orleans, LA, United States: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/cvpr52688.2022.01016
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2022 | Conference Paper | IST-REx-ID: 14168 |
Rahaman, N., Weiss, M., Locatello, F., Pal, C., Bengio, Y., Schölkopf, B., … Ballas, N. (2022). Neural attentive circuits. In 36th Conference on Neural Information Processing Systems (Vol. 35). New Orleans, United States.
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2022 | Conference Paper | IST-REx-ID: 14170 |
Dittadi, A., Papa, S., Vita, M. D., Schölkopf, B., Winther, O., & Locatello, F. (n.d.). Generalization and robustness implications in object-centric learning. In Proceedings of the 39th International Conference on Machine Learning (Vol. 2022, pp. 5221–5285). Baltimore, MD, United States: ML Research Press.
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2022 | Conference Paper | IST-REx-ID: 14172 |
Schott, L., Kügelgen, J. von, Träuble, F., Gehler, P., Russell, C., Bethge, M., … Brendel, W. (2022). Visual representation learning does not generalize strongly within the same domain. In 10th International Conference on Learning Representations. Virtual.
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2022 | Conference Paper | IST-REx-ID: 14107 |
Yao, J., Hong, Y., Wang, C., Xiao, T., He, T., Locatello, F., … Zhang, Z. (2022). Self-supervised amodal video object segmentation. In 36th Conference on Neural Information Processing Systems. New Orleans, LA, United States. https://doi.org/10.48550/arXiv.2210.12733
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2022 | Conference Paper | IST-REx-ID: 14171 |
Rolland, P., Cevher, V., Kleindessner, M., Russel, C., Schölkopf, B., Janzing, D., & Locatello, F. (2022). Score matching enables causal discovery of nonlinear additive noise models. In Proceedings of the 39th International Conference on Machine Learning (Vol. 162, pp. 18741–18753). Baltimore, MD, United States: ML Research Press.
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2022 | Conference Paper | IST-REx-ID: 14174 |
Dittadi, A., Träuble, F., Wüthrich, M., Widmaier, F., Gehler, P., Winther, O., … Bauer, S. (2022). The role of pretrained representations for the OOD generalization of reinforcement learning agents. In 10th International Conference on Learning Representations. Virtual.
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2022 | Conference Paper | IST-REx-ID: 14175 |
Makansi, O., Kügelgen, J. von, Locatello, F., Gehler, P., Janzing, D., Brox, T., & Schölkopf, B. (2022). You mostly walk alone: Analyzing feature attribution in trajectory prediction. In 10th International Conference on Learning Representations. Virtual.
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2022 | Preprint | IST-REx-ID: 14220 |
Mambelli, D., Träuble, F., Bauer, S., Schölkopf, B., & Locatello, F. (n.d.). Compositional multi-object reinforcement learning with linear relation networks. arXiv. https://doi.org/10.48550/arXiv.2201.13388
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2022 | Conference Paper | IST-REx-ID: 14215 |
Rahaman, N., Weiss, M., Träuble, F., Locatello, F., Lacoste, A., Bengio, Y., … Schölkopf, B. (n.d.). A general purpose neural architecture for geospatial systems. In 36th Conference on Neural Information Processing Systems. New Orleans, LA, United States.
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2022 | Preprint | IST-REx-ID: 14216 |
Norelli, A., Fumero, M., Maiorca, V., Moschella, L., Rodolà, E., & Locatello, F. (n.d.). ASIF: Coupled data turns unimodal models to multimodal without training. arXiv. https://doi.org/10.48550/arXiv.2210.01738
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2021 | Conference Paper | IST-REx-ID: 14177 |
Träuble, F., Creager, E., Kilbertus, N., Locatello, F., Dittadi, A., Goyal, A., … Bauer, S. (2021). On disentangled representations learned from correlated data. In Proceedings of the 38th International Conference on Machine Learning (Vol. 139, pp. 10401–10412). Virtual: ML Research Press.
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