Grounded object centric learning
A. Kori, F. Locatello, F.D.S. Ribeiro, F. Toni, B. Glocker, ArXiv (n.d.).
LibreCat: https://research-explorer.ista.ac.at/record/14948
DOI: 10.48550/arXiv.2307.09437
arXiv: 2307.09437

Sample complexity bounds for score-matching: Causal discovery and generative modeling
Z. Zhu, F. Locatello, V. Cevher, ArXiv (n.d.).
LibreCat: https://research-explorer.ista.ac.at/record/14953
DOI: 10.48550/arXiv.2310.18123
arXiv: 2310.18123

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.).
LibreCat: https://research-explorer.ista.ac.at/record/14954
DOI: 10.48550/arXiv.2310.13387
arXiv: 2310.13387

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.).
LibreCat: https://research-explorer.ista.ac.at/record/14210
DOI: 10.48550/arXiv.2304.07939
arXiv: 2304.07939

Rotating features for object discovery
S. Löwe, P. Lippe, F. Locatello, M. Welling, ArXiv (n.d.).
LibreCat: https://research-explorer.ista.ac.at/record/14207
DOI: 10.48550/arXiv.2306.00600
arXiv: 2306.00600

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.).
LibreCat: https://research-explorer.ista.ac.at/record/14963
DOI: 10.48550/arXiv.2309.00233
arXiv: 2309.00233

Shortcuts for causal discovery of nonlinear models by score matching
F. Montagna, N. Noceti, L. Rosasco, F. Locatello, ArXiv (n.d.).
LibreCat: https://research-explorer.ista.ac.at/record/14961
DOI: 10.48550/arXiv.2310.14246
arXiv: 2310.14246

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.).
LibreCat: https://research-explorer.ista.ac.at/record/14962
DOI: 10.48550/arXiv.2309.09858
arXiv: 2309.09858

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.
LibreCat: https://research-explorer.ista.ac.at/record/14958

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.
LibreCat: https://research-explorer.ista.ac.at/record/14974

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.
LibreCat: https://research-explorer.ista.ac.at/record/14173
arXiv: 2207.09239

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.
LibreCat: https://research-explorer.ista.ac.at/record/14106
arXiv: 2204.04440

 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.
LibreCat: https://research-explorer.ista.ac.at/record/14093
arXiv: 2202.13212

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.
LibreCat: https://research-explorer.ista.ac.at/record/14114
DOI: 10.1109/cvpr52688.2022.01016
arXiv: 2203.04913

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.
LibreCat: https://research-explorer.ista.ac.at/record/14168
arXiv: 2210.08031

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.
LibreCat: https://research-explorer.ista.ac.at/record/14170
arXiv: 2107.00637

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.
LibreCat: https://research-explorer.ista.ac.at/record/14172
arXiv: 2107.08221

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.
LibreCat: https://research-explorer.ista.ac.at/record/14107
DOI: 10.48550/arXiv.2210.12733
arXiv: 2210.12733

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.
LibreCat: https://research-explorer.ista.ac.at/record/14171
arXiv: 2203.04413

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.
LibreCat: https://research-explorer.ista.ac.at/record/14174
arXiv: 2107.05686