Francesco Locatello
Locatello Group
70 Publications
2024 | Published | Conference Paper | IST-REx-ID: 14213 |
Lao D, Hu Z, Locatello F, Yang Y, Soatto S. 2024. Divided attention: Unsupervised multi-object discovery with contextually separated slots. 1st Conference on Parsimony and Learning. CPAL: Conference on Parsimony and Learning.
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2023 | Published | Conference Paper | IST-REx-ID: 14105 |
Sinha S, Gehler P, Locatello F, Schiele B. 2023. TeST: Test-time Self-Training under distribution shift. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision. WACV: Winter Conference on Applications of Computer Vision.
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2023 | Submitted | Preprint | IST-REx-ID: 14207 |
Löwe S, Lippe P, Locatello F, Welling M. Rotating features for object discovery. arXiv, 2306.00600.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14208 |
Zhu Z, Liu F, Chrysos GG, Locatello F, Cevher V. 2023. Benign overfitting in deep neural networks under lazy training. Proceedings of the 40th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 202, 43105–43128.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14209 |
Burg MF, Wenzel F, Zietlow D, Horn M, Makansi O, Locatello F, Russell C. A data augmentation perspective on diffusion models and retrieval. arXiv, 2304.10253.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14210 |
Fumero M, Wenzel F, Zancato L, Achille A, Rodolà E, Soatto S, Schölkopf B, Locatello F. Leveraging sparse and shared feature activations for disentangled representation learning. arXiv, 2304.07939.
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2023 | Published | Conference Paper | IST-REx-ID: 14211 |
Montagna F, Noceti N, Rosasco L, Zhang K, Locatello F. 2023. Causal discovery with score matching on additive models with arbitrary noise. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14212 |
Montagna F, Noceti N, Rosasco L, Zhang K, Locatello F. 2023. Scalable causal discovery with score matching. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14214 |
Liu Y, Alahi A, Russell C, Horn M, Zietlow D, Schölkopf B, Locatello F. 2023. Causal triplet: An open challenge for intervention-centric causal representation learning. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14217 |
Moschella L, Maiorca V, Fumero M, Norelli A, Locatello F, Rodolà E. 2023. Relative representations enable zero-shot latent space communication. The 11th International Conference on Learning Representations. International Conference on Machine Learning Representations.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14218 |
Seitzer M, Horn M, Zadaianchuk A, Zietlow D, Xiao T, Carl-Johann Simon-Gabriel C-JS-G, He T, Zhang Z, Schölkopf B, Brox T, Locatello F. 2023. Bridging the gap to real-world object-centric learning. The 11th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14219 |
Zadaianchuk A, Kleindessner M, Zhu Y, Locatello F, Brox T. 2023. Unsupervised semantic segmentation with self-supervised object-centric representations. The 11th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14222 |
Tangemann M, Schneider S, Kügelgen J von, Locatello F, Gehler P, Brox T, Kümmerer M, Bethge M, Schölkopf B. 2023. Unsupervised object learning via common fate. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning, 2110.06562.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14333 |
Faller PM, Vankadara LC, Mastakouri AA, Locatello F, Janzing D. Self-compatibility: Evaluating causal discovery without ground truth. arXiv, 2307.09552.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14946 |
Yao D, Xu D, Lachapelle S, Magliacane S, Taslakian P, Martius G, Kügelgen J von, Locatello F. Multi-view causal representation learning with partial observability. arXiv, 2311.04056.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14948 |
Kori A, Locatello F, Ribeiro FDS, Toni F, Glocker B. Grounded object centric learning. arXiv, 2307.09437.
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2023 | Published | Journal Article | IST-REx-ID: 14949 |
Burg M, Wenzel F, Zietlow D, Horn M, Makansi O, Locatello F, Russell C. 2023. Image retrieval outperforms diffusion models on data augmentation. Journal of Machine Learning Research.
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2023 | Submitted | Preprint | IST-REx-ID: 14952 |
Maiorca V, Moschella L, Norelli A, Fumero M, Locatello F, Rodolà E. Latent space translation via semantic alignment. arXiv, 2311.00664.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14953 |
Zhu Z, Locatello F, Cevher V. Sample complexity bounds for score-matching: Causal discovery and generative modeling. arXiv, 2310.18123.
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2023 | Submitted | Preprint | IST-REx-ID: 14954 |
Montagna F, Mastakouri AA, Eulig E, Noceti N, Rosasco L, Janzing D, Aragam B, Locatello F. Assumption violations in causal discovery and the robustness of score matching. arXiv, 2310.13387.
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2023 | Published | 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. Causal Representation Learning Workshop at NeurIPS 2023. CRL: Causal Representation Learning Workshop at NeurIPS, 54.
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2023 | Submitted | Preprint | IST-REx-ID: 14961 |
Montagna F, Noceti N, Rosasco L, Locatello F. Shortcuts for causal discovery of nonlinear models by score matching. arXiv, 2310.14246.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14962 |
Fan K, Bai Z, Xiao T, Zietlow D, Horn M, Zhao Z, Carl-Johann Simon-Gabriel C-JS-G, Shou MZ, Locatello F, Schiele B, Brox T, Zhang Z, Fu Y, He T. Unsupervised open-vocabulary object localization in videos. arXiv, 2309.09858.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14963 |
Zhao Z, Wang J, Horn M, Ding Y, He T, Bai Z, Zietlow D, Carl-Johann Simon-Gabriel C-JS-G, Shuai B, Tu Z, Brox T, Schiele B, Fu Y, Locatello F, Zhang Z, Xiao T. Object-centric multiple object tracking. arXiv, 2309.00233.
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| arXiv
2022 | Published | 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. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics, PMLR, vol. 151, 8439–8457.
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| arXiv
2022 | Published | 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. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35, 16548–16562.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14107 |
Yao J, Hong Y, Wang C, Xiao T, He T, Locatello F, Wipf D, Fu Y, Zhang Z. 2022. Self-supervised amodal video object segmentation. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.
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| arXiv
2022 | Published | 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. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition, 10400–10411.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14168 |
Rahaman N, Weiss M, Locatello F, Pal C, Bengio Y, Schölkopf B, Li LE, Ballas N. 2022. Neural attentive circuits. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35.
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| arXiv
2022 | Submitted | Conference Paper | IST-REx-ID: 14170 |
Dittadi A, Papa S, Vita MD, Schölkopf B, Winther O, Locatello F. Generalization and robustness implications in object-centric learning. Proceedings of the 39th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 2022, 5221–5285.
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| arXiv
2022 | Published | 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. Proceedings of the 39th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 162, 18741–18753.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14172 |
Schott L, Kügelgen J von, Träuble F, Gehler P, Russell C, Bethge M, Schölkopf B, Locatello F, Brendel W. 2022. Visual representation learning does not generalize strongly within the same domain. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14173 |
Wenzel F, Dittadi A, Gehler PV, Carl-Johann Simon-Gabriel C-JS-G, Horn M, Zietlow D, Kernert D, Russell C, Brox T, Schiele B, Schölkopf B, Locatello F. 2022. Assaying out-of-distribution generalization in transfer learning. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35, 7181–7198.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14174 |
Dittadi A, Träuble F, Wüthrich M, Widmaier F, Gehler P, Winther O, Locatello F, Bachem O, Schölkopf B, Bauer S. 2022. The role of pretrained representations for the OOD generalization of reinforcement learning agents. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2022 | Published | 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. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2022 | Submitted | Conference Paper | IST-REx-ID: 14215 |
Rahaman N, Weiss M, Träuble F, Locatello F, Lacoste A, Bengio Y, Pal C, Li LE, Schölkopf B. A general purpose neural architecture for geospatial systems. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.
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| arXiv
2022 | Submitted | Preprint | IST-REx-ID: 14216 |
Norelli A, Fumero M, Maiorca V, Moschella L, Rodolà E, Locatello F. ASIF: Coupled data turns unimodal models to multimodal without training. arXiv, 2210.01738.
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| arXiv
2022 | Submitted | Preprint | IST-REx-ID: 14220 |
Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. arXiv, 2201.13388.
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| arXiv
2021 | Published | Journal Article | IST-REx-ID: 14117 |
Scholkopf B, Locatello F, Bauer S, Ke NR, Kalchbrenner N, Goyal A, Bengio Y. 2021. Toward causal representation learning. Proceedings of the IEEE. 109(5), 612–634.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14176 |
Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. 2021. Neighborhood contrastive learning applied to online patient monitoring. Proceedings of 38th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 139, 11964–11974.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14177 |
Träuble F, Creager E, Kilbertus N, Locatello F, Dittadi A, Goyal A, Schölkopf B, Bauer S. 2021. On disentangled representations learned from correlated data. Proceedings of the 38th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 139, 10401–10412.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14178 |
Dittadi A, Träuble F, Locatello F, Wüthrich M, Agrawal V, Winther O, Bauer S, Schölkopf B. 2021. On the transfer of disentangled representations in realistic settings. The Ninth International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14179 |
Kügelgen J von, Sharma Y, Gresele L, Brendel W, Schölkopf B, Besserve M, Locatello F. 2021. Self-supervised learning with data augmentations provably isolates content from style. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 16451–16467.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14180 |
Rahaman N, Gondal MW, Joshi S, Gehler P, Bengio Y, Locatello F, Schölkopf B. 2021. Dynamic inference with neural interpreters. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 10985–10998.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14181 |
Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. 2021. Boosting variational inference with locally adaptive step-sizes. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI: International Joint Conference on Artificial Intelligence, 2337–2343.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14182 |
Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler P. 2021. Backward-compatible prediction updates: A probabilistic approach. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 116–128.
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| arXiv
2021 | Submitted | Preprint | IST-REx-ID: 14221 |
Locatello F. Enforcing and discovering structure in machine learning. arXiv, 2111.13693.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14332
Träuble F, Dittadi A, Wuthrich M, Widmaier F, Gehler PV, Winther O, Locatello F, Bachem O, Schölkopf B, Bauer S. 2021. Representation learning for out-of-distribution generalization in reinforcement learning. ICML 2021 Workshop on Unsupervised Reinforcement Learning. ICML: International Conference on Machine Learning.
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2020 | Published | Journal Article | IST-REx-ID: 14125 |
Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired feature sets. Bioinformatics. 36(Supplement_2), i919–i927.
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| PubMed | Europe PMC
2020 | Published | Conference Paper | IST-REx-ID: 14186 |
Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2020. A commentary on the unsupervised learning of disentangled representations. The 34th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 34, 13681–13684.
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 14187 |
Négiar G, Dresdner G, Tsai A, Ghaoui LE, Locatello F, Freund RM, Pedregosa F. 2020. Stochastic Frank-Wolfe for constrained finite-sum minimization. Proceedings of the 37th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 119, 7253–7262.
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 14188 |
Locatello F, Poole B, Rätsch G, Schölkopf B, Bachem O, Tschannen M. 2020. Weakly-supervised disentanglement without compromises. Proceedings of the 37th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 119, 6348–6359.
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| arXiv
2020 | Published | Journal Article | IST-REx-ID: 14195 |
Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2020. A sober look at the unsupervised learning of disentangled representations and their evaluation. Journal of Machine Learning Research. 21, 209.
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 14326 |
Locatello F, Weissenborn D, Unterthiner T, Mahendran A, Heigold G, Uszkoreit J, Dosovitskiy A, Kipf T. 2020. Object-centric learning with slot attention. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 33, 11525–11538.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14184 |
Locatello F, Tschannen M, Bauer S, Rätsch G, Schölkopf B, Bachem O. 2019. Disentangling factors of variation using few labels. 8th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14189 |
Gresele L, Rubenstein PK, Mehrjou A, Locatello F, Schölkopf B. 2019. The incomplete Rosetta Stone problem: Identifiability results for multi-view nonlinear ICA. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence. UAI: Uncertainty in Artificial Intelligence, PMLR, vol. 115, 217–227.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14190 |
Gondal MW, Wüthrich M, Miladinović Đ, Locatello F, Breidt M, Volchkov V, Akpo J, Bachem O, Schölkopf B, Bauer S. 2019. On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14191 |
Locatello F, Yurtsever A, Fercoq O, Cevher V. 2019. Stochastic Frank-Wolfe for composite convex minimization. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32, 14291–14301.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14193 |
Steenkiste S van, Locatello F, Schmidhuber J, Bachem O. 2019. Are disentangled representations helpful for abstract visual reasoning? Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14197 |
Locatello F, Abbati G, Rainforth T, Bauer S, Schölkopf B, Bachem O. 2019. On the fairness of disentangled representations. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32, 14611–14624.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14200 |
Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2019. Challenging common assumptions in the unsupervised learning of disentangled representations. Proceedings of the 36th International Conference on Machine Learning. International Conference on Machine Learning vol. 97, 4114–4124.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14198 |
Fortuin V, Hüser M, Locatello F, Strathmann H, Rätsch G. 2018. SOM-VAE: Interpretable discrete representation learning on time series. International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14201 |
Locatello F, Khanna R, Ghosh J, Rätsch G. 2018. Boosting variational inference: An optimization perspective. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics, PMLR, vol. 84, 464–472.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14202 |
Locatello F, Dresdner G, Khanna R, Valera I, Rätsch G. 2018. Boosting black box variational inference. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 31.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14203 |
Yurtsever A, Fercoq O, Locatello F, Cevher V. 2018. A conditional gradient framework for composite convex minimization with applications to semidefinite programming. Proceedings of the 35th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 80, 5727–5736.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14204 |
Locatello F, Raj A, Karimireddy SP, Rätsch G, Schölkopf B, Stich SU, Jaggi M. 2018. On matching pursuit and coordinate descent. Proceedings of the 35th International Conference on Machine Learning. , PMLR, vol. 80, 3198–3207.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14224 |
Locatello F, Vincent D, Tolstikhin I, Ratsch G, Gelly S, Scholkopf B. 2018. Clustering meets implicit generative models. 6th International Conference on Learning Representations. International Conference on Machine Learning.
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| arXiv
2018 | Submitted | Preprint | IST-REx-ID: 14327 |
Locatello F, Vincent D, Tolstikhin I, Rätsch G, Gelly S, Schölkopf B. Competitive training of mixtures of independent deep generative models. arXiv, 1804.11130.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 14205 |
Locatello F, Khanna R, Tschannen M, Jaggi M. 2017. A unified optimization view on generalized matching pursuit and Frank-Wolfe. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics vol. 54, 860–868.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 14206 |
Locatello F, Tschannen M, Rätsch G, Jaggi M. 2017. Greedy algorithms for cone constrained optimization with convergence guarantees. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.
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| arXiv
Grants
70 Publications
2024 | Published | Conference Paper | IST-REx-ID: 14213 |
Lao D, Hu Z, Locatello F, Yang Y, Soatto S. 2024. Divided attention: Unsupervised multi-object discovery with contextually separated slots. 1st Conference on Parsimony and Learning. CPAL: Conference on Parsimony and Learning.
[Published Version]
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14105 |
Sinha S, Gehler P, Locatello F, Schiele B. 2023. TeST: Test-time Self-Training under distribution shift. 2023 IEEE/CVF Winter Conference on Applications of Computer Vision. WACV: Winter Conference on Applications of Computer Vision.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14207 |
Löwe S, Lippe P, Locatello F, Welling M. Rotating features for object discovery. arXiv, 2306.00600.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14208 |
Zhu Z, Liu F, Chrysos GG, Locatello F, Cevher V. 2023. Benign overfitting in deep neural networks under lazy training. Proceedings of the 40th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 202, 43105–43128.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14209 |
Burg MF, Wenzel F, Zietlow D, Horn M, Makansi O, Locatello F, Russell C. A data augmentation perspective on diffusion models and retrieval. arXiv, 2304.10253.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14210 |
Fumero M, Wenzel F, Zancato L, Achille A, Rodolà E, Soatto S, Schölkopf B, Locatello F. Leveraging sparse and shared feature activations for disentangled representation learning. arXiv, 2304.07939.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14211 |
Montagna F, Noceti N, Rosasco L, Zhang K, Locatello F. 2023. Causal discovery with score matching on additive models with arbitrary noise. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14212 |
Montagna F, Noceti N, Rosasco L, Zhang K, Locatello F. 2023. Scalable causal discovery with score matching. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14214 |
Liu Y, Alahi A, Russell C, Horn M, Zietlow D, Schölkopf B, Locatello F. 2023. Causal triplet: An open challenge for intervention-centric causal representation learning. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14217 |
Moschella L, Maiorca V, Fumero M, Norelli A, Locatello F, Rodolà E. 2023. Relative representations enable zero-shot latent space communication. The 11th International Conference on Learning Representations. International Conference on Machine Learning Representations.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14218 |
Seitzer M, Horn M, Zadaianchuk A, Zietlow D, Xiao T, Carl-Johann Simon-Gabriel C-JS-G, He T, Zhang Z, Schölkopf B, Brox T, Locatello F. 2023. Bridging the gap to real-world object-centric learning. The 11th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14219 |
Zadaianchuk A, Kleindessner M, Zhu Y, Locatello F, Brox T. 2023. Unsupervised semantic segmentation with self-supervised object-centric representations. The 11th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14222 |
Tangemann M, Schneider S, Kügelgen J von, Locatello F, Gehler P, Brox T, Kümmerer M, Bethge M, Schölkopf B. 2023. Unsupervised object learning via common fate. 2nd Conference on Causal Learning and Reasoning. CLeaR: Conference on Causal Learning and Reasoning, 2110.06562.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14333 |
Faller PM, Vankadara LC, Mastakouri AA, Locatello F, Janzing D. Self-compatibility: Evaluating causal discovery without ground truth. arXiv, 2307.09552.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14946 |
Yao D, Xu D, Lachapelle S, Magliacane S, Taslakian P, Martius G, Kügelgen J von, Locatello F. Multi-view causal representation learning with partial observability. arXiv, 2311.04056.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14948 |
Kori A, Locatello F, Ribeiro FDS, Toni F, Glocker B. Grounded object centric learning. arXiv, 2307.09437.
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| arXiv
2023 | Published | Journal Article | IST-REx-ID: 14949 |
Burg M, Wenzel F, Zietlow D, Horn M, Makansi O, Locatello F, Russell C. 2023. Image retrieval outperforms diffusion models on data augmentation. Journal of Machine Learning Research.
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2023 | Submitted | Preprint | IST-REx-ID: 14952 |
Maiorca V, Moschella L, Norelli A, Fumero M, Locatello F, Rodolà E. Latent space translation via semantic alignment. arXiv, 2311.00664.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14953 |
Zhu Z, Locatello F, Cevher V. Sample complexity bounds for score-matching: Causal discovery and generative modeling. arXiv, 2310.18123.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14954 |
Montagna F, Mastakouri AA, Eulig E, Noceti N, Rosasco L, Janzing D, Aragam B, Locatello F. Assumption violations in causal discovery and the robustness of score matching. arXiv, 2310.13387.
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| arXiv
2023 | Published | 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. Causal Representation Learning Workshop at NeurIPS 2023. CRL: Causal Representation Learning Workshop at NeurIPS, 54.
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2023 | Submitted | Preprint | IST-REx-ID: 14961 |
Montagna F, Noceti N, Rosasco L, Locatello F. Shortcuts for causal discovery of nonlinear models by score matching. arXiv, 2310.14246.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14962 |
Fan K, Bai Z, Xiao T, Zietlow D, Horn M, Zhao Z, Carl-Johann Simon-Gabriel C-JS-G, Shou MZ, Locatello F, Schiele B, Brox T, Zhang Z, Fu Y, He T. Unsupervised open-vocabulary object localization in videos. arXiv, 2309.09858.
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| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14963 |
Zhao Z, Wang J, Horn M, Ding Y, He T, Bai Z, Zietlow D, Carl-Johann Simon-Gabriel C-JS-G, Shuai B, Tu Z, Brox T, Schiele B, Fu Y, Locatello F, Zhang Z, Xiao T. Object-centric multiple object tracking. arXiv, 2309.00233.
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| arXiv
2022 | Published | 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. Proceedings of the 25th International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics, PMLR, vol. 151, 8439–8457.
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| arXiv
2022 | Published | 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. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35, 16548–16562.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14107 |
Yao J, Hong Y, Wang C, Xiao T, He T, Locatello F, Wipf D, Fu Y, Zhang Z. 2022. Self-supervised amodal video object segmentation. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.
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| arXiv
2022 | Published | 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. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition, 10400–10411.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14168 |
Rahaman N, Weiss M, Locatello F, Pal C, Bengio Y, Schölkopf B, Li LE, Ballas N. 2022. Neural attentive circuits. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35.
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| arXiv
2022 | Submitted | Conference Paper | IST-REx-ID: 14170 |
Dittadi A, Papa S, Vita MD, Schölkopf B, Winther O, Locatello F. Generalization and robustness implications in object-centric learning. Proceedings of the 39th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 2022, 5221–5285.
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| arXiv
2022 | Published | 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. Proceedings of the 39th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 162, 18741–18753.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14172 |
Schott L, Kügelgen J von, Träuble F, Gehler P, Russell C, Bethge M, Schölkopf B, Locatello F, Brendel W. 2022. Visual representation learning does not generalize strongly within the same domain. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14173 |
Wenzel F, Dittadi A, Gehler PV, Carl-Johann Simon-Gabriel C-JS-G, Horn M, Zietlow D, Kernert D, Russell C, Brox T, Schiele B, Schölkopf B, Locatello F. 2022. Assaying out-of-distribution generalization in transfer learning. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35, 7181–7198.
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| arXiv
2022 | Published | Conference Paper | IST-REx-ID: 14174 |
Dittadi A, Träuble F, Wüthrich M, Widmaier F, Gehler P, Winther O, Locatello F, Bachem O, Schölkopf B, Bauer S. 2022. The role of pretrained representations for the OOD generalization of reinforcement learning agents. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2022 | Published | 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. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2022 | Submitted | Conference Paper | IST-REx-ID: 14215 |
Rahaman N, Weiss M, Träuble F, Locatello F, Lacoste A, Bengio Y, Pal C, Li LE, Schölkopf B. A general purpose neural architecture for geospatial systems. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.
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| arXiv
2022 | Submitted | Preprint | IST-REx-ID: 14216 |
Norelli A, Fumero M, Maiorca V, Moschella L, Rodolà E, Locatello F. ASIF: Coupled data turns unimodal models to multimodal without training. arXiv, 2210.01738.
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| arXiv
2022 | Submitted | Preprint | IST-REx-ID: 14220 |
Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. arXiv, 2201.13388.
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| arXiv
2021 | Published | Journal Article | IST-REx-ID: 14117 |
Scholkopf B, Locatello F, Bauer S, Ke NR, Kalchbrenner N, Goyal A, Bengio Y. 2021. Toward causal representation learning. Proceedings of the IEEE. 109(5), 612–634.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14176 |
Yèche H, Dresdner G, Locatello F, Hüser M, Rätsch G. 2021. Neighborhood contrastive learning applied to online patient monitoring. Proceedings of 38th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 139, 11964–11974.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14177 |
Träuble F, Creager E, Kilbertus N, Locatello F, Dittadi A, Goyal A, Schölkopf B, Bauer S. 2021. On disentangled representations learned from correlated data. Proceedings of the 38th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 139, 10401–10412.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14178 |
Dittadi A, Träuble F, Locatello F, Wüthrich M, Agrawal V, Winther O, Bauer S, Schölkopf B. 2021. On the transfer of disentangled representations in realistic settings. The Ninth International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14179 |
Kügelgen J von, Sharma Y, Gresele L, Brendel W, Schölkopf B, Besserve M, Locatello F. 2021. Self-supervised learning with data augmentations provably isolates content from style. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 16451–16467.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14180 |
Rahaman N, Gondal MW, Joshi S, Gehler P, Bengio Y, Locatello F, Schölkopf B. 2021. Dynamic inference with neural interpreters. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 10985–10998.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14181 |
Dresdner G, Shekhar S, Pedregosa F, Locatello F, Rätsch G. 2021. Boosting variational inference with locally adaptive step-sizes. Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. IJCAI: International Joint Conference on Artificial Intelligence, 2337–2343.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14182 |
Träuble F, Kügelgen J von, Kleindessner M, Locatello F, Schölkopf B, Gehler P. 2021. Backward-compatible prediction updates: A probabilistic approach. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 34, 116–128.
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| arXiv
2021 | Submitted | Preprint | IST-REx-ID: 14221 |
Locatello F. Enforcing and discovering structure in machine learning. arXiv, 2111.13693.
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| arXiv
2021 | Published | Conference Paper | IST-REx-ID: 14332
Träuble F, Dittadi A, Wuthrich M, Widmaier F, Gehler PV, Winther O, Locatello F, Bachem O, Schölkopf B, Bauer S. 2021. Representation learning for out-of-distribution generalization in reinforcement learning. ICML 2021 Workshop on Unsupervised Reinforcement Learning. ICML: International Conference on Machine Learning.
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2020 | Published | Journal Article | IST-REx-ID: 14125 |
Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired feature sets. Bioinformatics. 36(Supplement_2), i919–i927.
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| PubMed | Europe PMC
2020 | Published | Conference Paper | IST-REx-ID: 14186 |
Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2020. A commentary on the unsupervised learning of disentangled representations. The 34th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 34, 13681–13684.
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 14187 |
Négiar G, Dresdner G, Tsai A, Ghaoui LE, Locatello F, Freund RM, Pedregosa F. 2020. Stochastic Frank-Wolfe for constrained finite-sum minimization. Proceedings of the 37th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 119, 7253–7262.
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 14188 |
Locatello F, Poole B, Rätsch G, Schölkopf B, Bachem O, Tschannen M. 2020. Weakly-supervised disentanglement without compromises. Proceedings of the 37th International Conference on Machine Learning. International Conference on Machine Learning, PMLR, vol. 119, 6348–6359.
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| arXiv
2020 | Published | Journal Article | IST-REx-ID: 14195 |
Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2020. A sober look at the unsupervised learning of disentangled representations and their evaluation. Journal of Machine Learning Research. 21, 209.
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| arXiv
2020 | Published | Conference Paper | IST-REx-ID: 14326 |
Locatello F, Weissenborn D, Unterthiner T, Mahendran A, Heigold G, Uszkoreit J, Dosovitskiy A, Kipf T. 2020. Object-centric learning with slot attention. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 33, 11525–11538.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14184 |
Locatello F, Tschannen M, Bauer S, Rätsch G, Schölkopf B, Bachem O. 2019. Disentangling factors of variation using few labels. 8th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14189 |
Gresele L, Rubenstein PK, Mehrjou A, Locatello F, Schölkopf B. 2019. The incomplete Rosetta Stone problem: Identifiability results for multi-view nonlinear ICA. Proceedings of the 35th Conference on Uncertainty in Artificial Intelligence. UAI: Uncertainty in Artificial Intelligence, PMLR, vol. 115, 217–227.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14190 |
Gondal MW, Wüthrich M, Miladinović Đ, Locatello F, Breidt M, Volchkov V, Akpo J, Bachem O, Schölkopf B, Bauer S. 2019. On the transfer of inductive bias from simulation to the real world: a new disentanglement dataset. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14191 |
Locatello F, Yurtsever A, Fercoq O, Cevher V. 2019. Stochastic Frank-Wolfe for composite convex minimization. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32, 14291–14301.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14193 |
Steenkiste S van, Locatello F, Schmidhuber J, Bachem O. 2019. Are disentangled representations helpful for abstract visual reasoning? Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14197 |
Locatello F, Abbati G, Rainforth T, Bauer S, Schölkopf B, Bachem O. 2019. On the fairness of disentangled representations. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 32, 14611–14624.
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| arXiv
2019 | Published | Conference Paper | IST-REx-ID: 14200 |
Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2019. Challenging common assumptions in the unsupervised learning of disentangled representations. Proceedings of the 36th International Conference on Machine Learning. International Conference on Machine Learning vol. 97, 4114–4124.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14198 |
Fortuin V, Hüser M, Locatello F, Strathmann H, Rätsch G. 2018. SOM-VAE: Interpretable discrete representation learning on time series. International Conference on Learning Representations. ICLR: International Conference on Learning Representations.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14201 |
Locatello F, Khanna R, Ghosh J, Rätsch G. 2018. Boosting variational inference: An optimization perspective. Proceedings of the 21st International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics, PMLR, vol. 84, 464–472.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14202 |
Locatello F, Dresdner G, Khanna R, Valera I, Rätsch G. 2018. Boosting black box variational inference. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems vol. 31.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14203 |
Yurtsever A, Fercoq O, Locatello F, Cevher V. 2018. A conditional gradient framework for composite convex minimization with applications to semidefinite programming. Proceedings of the 35th International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 80, 5727–5736.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14204 |
Locatello F, Raj A, Karimireddy SP, Rätsch G, Schölkopf B, Stich SU, Jaggi M. 2018. On matching pursuit and coordinate descent. Proceedings of the 35th International Conference on Machine Learning. , PMLR, vol. 80, 3198–3207.
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| arXiv
2018 | Published | Conference Paper | IST-REx-ID: 14224 |
Locatello F, Vincent D, Tolstikhin I, Ratsch G, Gelly S, Scholkopf B. 2018. Clustering meets implicit generative models. 6th International Conference on Learning Representations. International Conference on Machine Learning.
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| arXiv
2018 | Submitted | Preprint | IST-REx-ID: 14327 |
Locatello F, Vincent D, Tolstikhin I, Rätsch G, Gelly S, Schölkopf B. Competitive training of mixtures of independent deep generative models. arXiv, 1804.11130.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 14205 |
Locatello F, Khanna R, Tschannen M, Jaggi M. 2017. A unified optimization view on generalized matching pursuit and Frank-Wolfe. Proceedings of the 20th International Conference on Artificial Intelligence and Statistics. AISTATS: Conference on Artificial Intelligence and Statistics vol. 54, 860–868.
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| arXiv
2017 | Published | Conference Paper | IST-REx-ID: 14206 |
Locatello F, Tschannen M, Rätsch G, Jaggi M. 2017. Greedy algorithms for cone constrained optimization with convergence guarantees. Advances in Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.
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| arXiv