Francesco Locatello

Locatello Group

70 Publikationen

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[70]
2024 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14213 | OA
Lao, Dong, Divided attention: Unsupervised multi-object discovery with contextually separated slots. 1st Conference on Parsimony and Learning. 2024
[Published Version] View | Dateien verfügbar | arXiv
 
[69]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14105 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[68]
2023 | Eingereicht | Preprint | IST-REx-ID: 14207 | OA
Löwe S, Lippe P, Locatello F, Welling M. Rotating features for object discovery. arXiv, 2306.00600.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[67]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14208 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[66]
2023 | Eingereicht | Preprint | IST-REx-ID: 14209 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[65]
2023 | Eingereicht | Preprint | IST-REx-ID: 14210 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[64]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14211 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[63]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14212 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[62]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14214 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[61]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14217 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[60]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14218 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[59]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14219 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[58]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14222 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[57]
2023 | Eingereicht | Preprint | IST-REx-ID: 14333 | OA
Faller PM, Vankadara LC, Mastakouri AA, Locatello F, Janzing D. Self-compatibility: Evaluating causal discovery without ground truth. arXiv, 2307.09552.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[56]
2023 | Eingereicht | Preprint | IST-REx-ID: 14946 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[55]
2023 | Eingereicht | Preprint | IST-REx-ID: 14948 | OA
Kori A, Locatello F, Ribeiro FDS, Toni F, Glocker B. Grounded object centric learning. arXiv, 2307.09437.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[54]
2023 | Veröffentlicht | Zeitschriftenaufsatz | IST-REx-ID: 14949 | OA
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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[53]
2023 | Eingereicht | Preprint | IST-REx-ID: 14952 | OA
Maiorca V, Moschella L, Norelli A, Fumero M, Locatello F, Rodolà E. Latent space translation via semantic alignment. arXiv, 2311.00664.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[52]
2023 | Eingereicht | Preprint | IST-REx-ID: 14953 | OA
Zhu Z, Locatello F, Cevher V. Sample complexity bounds for score-matching: Causal discovery and generative modeling. arXiv, 2310.18123.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[51]
2023 | Eingereicht | Preprint | IST-REx-ID: 14954 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[50]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14958 | OA
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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[49]
2023 | Eingereicht | Preprint | IST-REx-ID: 14961 | OA
Montagna F, Noceti N, Rosasco L, Locatello F. Shortcuts for causal discovery of nonlinear models by score matching. arXiv, 2310.14246.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[48]
2023 | Eingereicht | Preprint | IST-REx-ID: 14962 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[47]
2023 | Eingereicht | Preprint | IST-REx-ID: 14963 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[46]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14093 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[45]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14106 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[44]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14107 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[43]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14114 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[42]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14168 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[41]
2022 | Eingereicht | Konferenzbeitrag | IST-REx-ID: 14170 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[40]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14171 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[39]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14172 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[38]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14173 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[37]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14174 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[36]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14175 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[35]
2022 | Eingereicht | Konferenzbeitrag | IST-REx-ID: 14215 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[34]
2022 | Eingereicht | Preprint | IST-REx-ID: 14216 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[33]
2022 | Eingereicht | Preprint | IST-REx-ID: 14220 | OA
Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. arXiv, 2201.13388.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[32]
2021 | Veröffentlicht | Zeitschriftenaufsatz | IST-REx-ID: 14117 | OA
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.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
[31]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14176 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[30]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14177 | OA
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.
[Published Version] View | Download Published Version (ext.) | arXiv
 
[29]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14178 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[28]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14179 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[27]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14180 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[26]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14181 | OA
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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[25]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14182 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[24]
2021 | Eingereicht | Preprint | IST-REx-ID: 14221 | OA
Locatello F. Enforcing and discovering structure in machine learning. arXiv, 2111.13693.
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[23]
2021 | Veröffentlicht | Konferenzbeitrag | 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.
View
 
[22]
2020 | Veröffentlicht | Zeitschriftenaufsatz | IST-REx-ID: 14125 | OA
Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired feature sets. Bioinformatics. 36(Supplement_2), i919–i927.
[Published Version] View | Dateien verfügbar | DOI | Download Published Version (ext.) | PubMed | Europe PMC
 
[21]
2020 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14186 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[20]
2020 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14187 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[19]
2020 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14188 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[18]
2020 | Veröffentlicht | Zeitschriftenaufsatz | IST-REx-ID: 14195 | OA
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.
[Published Version] View | Download Published Version (ext.) | arXiv
 
[17]
2020 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14326 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[16]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14184 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[15]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14189 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[14]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14190 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[13]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14191 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[12]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14193 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[11]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14197 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[10]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14200 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[9]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14198 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[8]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14201 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[7]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14202 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[6]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14203 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[5]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14204 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[4]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14224 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[3]
2018 | Eingereicht | Preprint | IST-REx-ID: 14327 | OA
Locatello F, Vincent D, Tolstikhin I, Rätsch G, Gelly S, Schölkopf B. Competitive training of mixtures of independent deep generative models. arXiv, 1804.11130.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[2]
2017 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14205 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[1]
2017 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14206 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
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[70]
2024 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14213 | OA
Lao, Dong, Divided attention: Unsupervised multi-object discovery with contextually separated slots. 1st Conference on Parsimony and Learning. 2024
[Published Version] View | Dateien verfügbar | arXiv
 
[69]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14105 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[68]
2023 | Eingereicht | Preprint | IST-REx-ID: 14207 | OA
Löwe S, Lippe P, Locatello F, Welling M. Rotating features for object discovery. arXiv, 2306.00600.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[67]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14208 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[66]
2023 | Eingereicht | Preprint | IST-REx-ID: 14209 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[65]
2023 | Eingereicht | Preprint | IST-REx-ID: 14210 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[64]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14211 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[63]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14212 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[62]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14214 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[61]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14217 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[60]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14218 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[59]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14219 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[58]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14222 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[57]
2023 | Eingereicht | Preprint | IST-REx-ID: 14333 | OA
Faller PM, Vankadara LC, Mastakouri AA, Locatello F, Janzing D. Self-compatibility: Evaluating causal discovery without ground truth. arXiv, 2307.09552.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[56]
2023 | Eingereicht | Preprint | IST-REx-ID: 14946 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[55]
2023 | Eingereicht | Preprint | IST-REx-ID: 14948 | OA
Kori A, Locatello F, Ribeiro FDS, Toni F, Glocker B. Grounded object centric learning. arXiv, 2307.09437.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[54]
2023 | Veröffentlicht | Zeitschriftenaufsatz | IST-REx-ID: 14949 | OA
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.
[Published Version] View | Dateien verfügbar | Download Published Version (ext.)
 
[53]
2023 | Eingereicht | Preprint | IST-REx-ID: 14952 | OA
Maiorca V, Moschella L, Norelli A, Fumero M, Locatello F, Rodolà E. Latent space translation via semantic alignment. arXiv, 2311.00664.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[52]
2023 | Eingereicht | Preprint | IST-REx-ID: 14953 | OA
Zhu Z, Locatello F, Cevher V. Sample complexity bounds for score-matching: Causal discovery and generative modeling. arXiv, 2310.18123.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[51]
2023 | Eingereicht | Preprint | IST-REx-ID: 14954 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[50]
2023 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14958 | OA
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.
[Published Version] View | Dateien verfügbar | Download Published Version (ext.)
 
[49]
2023 | Eingereicht | Preprint | IST-REx-ID: 14961 | OA
Montagna F, Noceti N, Rosasco L, Locatello F. Shortcuts for causal discovery of nonlinear models by score matching. arXiv, 2310.14246.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[48]
2023 | Eingereicht | Preprint | IST-REx-ID: 14962 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[47]
2023 | Eingereicht | Preprint | IST-REx-ID: 14963 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[46]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14093 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[45]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14106 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[44]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14107 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[43]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14114 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[42]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14168 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[41]
2022 | Eingereicht | Konferenzbeitrag | IST-REx-ID: 14170 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[40]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14171 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[39]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14172 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[38]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14173 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[37]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14174 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[36]
2022 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14175 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[35]
2022 | Eingereicht | Konferenzbeitrag | IST-REx-ID: 14215 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[34]
2022 | Eingereicht | Preprint | IST-REx-ID: 14216 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[33]
2022 | Eingereicht | Preprint | IST-REx-ID: 14220 | OA
Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. arXiv, 2201.13388.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[32]
2021 | Veröffentlicht | Zeitschriftenaufsatz | IST-REx-ID: 14117 | OA
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.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
[31]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14176 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[30]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14177 | OA
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.
[Published Version] View | Download Published Version (ext.) | arXiv
 
[29]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14178 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[28]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14179 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[27]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14180 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[26]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14181 | OA
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.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
[25]
2021 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14182 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[24]
2021 | Eingereicht | Preprint | IST-REx-ID: 14221 | OA
Locatello F. Enforcing and discovering structure in machine learning. arXiv, 2111.13693.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[23]
2021 | Veröffentlicht | Konferenzbeitrag | 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.
View
 
[22]
2020 | Veröffentlicht | Zeitschriftenaufsatz | IST-REx-ID: 14125 | OA
Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired feature sets. Bioinformatics. 36(Supplement_2), i919–i927.
[Published Version] View | Dateien verfügbar | DOI | Download Published Version (ext.) | PubMed | Europe PMC
 
[21]
2020 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14186 | OA
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.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[20]
2020 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14187 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[19]
2020 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14188 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[18]
2020 | Veröffentlicht | Zeitschriftenaufsatz | IST-REx-ID: 14195 | OA
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.
[Published Version] View | Download Published Version (ext.) | arXiv
 
[17]
2020 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14326 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[16]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14184 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[15]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14189 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[14]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14190 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[13]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14191 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[12]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14193 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[11]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14197 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[10]
2019 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14200 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[9]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14198 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[8]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14201 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[7]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14202 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[6]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14203 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[5]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14204 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[4]
2018 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14224 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[3]
2018 | Eingereicht | Preprint | IST-REx-ID: 14327 | OA
Locatello F, Vincent D, Tolstikhin I, Rätsch G, Gelly S, Schölkopf B. Competitive training of mixtures of independent deep generative models. arXiv, 1804.11130.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
[2]
2017 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14205 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
[1]
2017 | Veröffentlicht | Konferenzbeitrag | IST-REx-ID: 14206 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
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