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83 Publications


2024 | Published | Conference Paper | IST-REx-ID: 18847 | OA
Cadei R, Lindorfer L, Cremer S, Schmid C, Locatello F. Smoke and mirrors in causal downstream tasks. In: ICML 2024 Workshop AI4Science. Vol 38. Curran Associates; 2024.
[Published Version] View | Files available | arXiv
 

2024 | Research Data Reference | IST-REx-ID: 18895 | OA
Cadei R, Locatello F, Cremer S, Lindorfer L, Schmid C. ISTAnt. 2024. doi:10.6084/M9.FIGSHARE.26484934.V2
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 

2024 | Published | Conference Paper | IST-REx-ID: 18956 | OA
Demirel B, Ozkan H. Decompl: Decompositional learning with attention pooling for group activity recognition from a single volleyball image. In: 2024 IEEE International Conference on Image Processing. IEEE; 2024:977-983. doi:10.1109/icip51287.2024.10647499
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18964 | OA
Fan K, Bai Z, Xiao T, et al. Adaptive slot attention: Object discovery with dynamic slot number. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE; 2024. doi:10.1109/cvpr52733.2024.02176
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18971 | OA
Arefin R, Zhang Y, Baratin A, et al. Unsupervised concept discovery mitigates spurious correlations. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:1672-1688.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18996 | OA
Chen T, Bello K, Locatello F, Aragam B, Ravikumar PK. Identifying general mechanism shifts in linear causal representations. In: 38th Conference on Neural Information Processing Systems. Vol 38. Curran Associates; 2024.
[Published Version] View | Files available | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 19010 | OA
Yao D, Rancati D, Cadei R, Fumero M, Locatello F. Unifying causal representation learning with the invariance principle. In: 38th Conference on Neural Information Processing Systems. Vol 38. Curran Associates; 2024.
[Published Version] View | Files available | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 19005 | OA
Yao D, Muller CJ, Locatello F. Marrying causal representation learning with dynamical systems for science. In: 38th Conference on Neural Information Processing Systems. Vol 38. Curran Associates; 2024.
[Published Version] View | Files available | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 19007 | OA
Kori A, Locatello F, Santhirasekaram A, Toni F, Glocker B, De Sousa Ribeiro F. Identifiable object-centric representation learning via probabilistic slot attention. In: 38th Conference on Neural Information Processing Systems. Vol 38. Curran Associates; 2024.
[Published Version] View | Files available | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 14946 | OA
Yao D, Xu D, Lachapelle S, et al. Multi-view causal representation learning with partial observability. In: 12th International Conference on Learning Representations. Curran Associates; 2024.
[Published Version] View | Files available | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 14213 | OA
Lao D, Hu Z, Locatello F, Yang Y, Soatto S. Divided attention: Unsupervised multi-object discovery with contextually separated slots. In: 1st Conference on Parsimony and Learning. ; 2024.
[Published Version] View | Files available | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18114 | OA
Pervez AA, Locatello F, Gavves E. Mechanistic neural networks for scientific machine learning. In: Proceedings of the 41st International Conference on Machine Learning. Vol 235. ML Research Press; 2024:40484-40501.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2023 | Patent | IST-REx-ID: 14965 | OA
Ficek J, Lehmann K-V, Locatello F, Raetsch G, Stark S. Methods of determining correspondences between biological properties of cells. 2023.
[Published Version] View | Files available
 

2023 | Published | Conference Paper | 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. In: 37th Conference on Neural Information Processing Systems. Vol 36. Curran Associates; 2023:15303-15319.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2023 | Published | Conference Paper | IST-REx-ID: 14958 | OA
Xu D, Yao D, Lachapelle S, et al. A sparsity principle for partially observable causal representation learning. In: Causal Representation Learning Workshop at NeurIPS 2023. OpenReview; 2023.
[Published Version] View | Files available | Download Published Version (ext.)
 

2023 | Published | Conference Paper | IST-REx-ID: 14105 | OA
Sinha S, Gehler P, Locatello F, Schiele B. TeST: Test-time Self-Training under distribution shift. In: 2023 IEEE/CVF Winter Conference on Applications of Computer Vision. Institute of Electrical and Electronics Engineers; 2023. doi:10.1109/wacv56688.2023.00278
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Submitted | Preprint | IST-REx-ID: 14207 | OA
Löwe S, Lippe P, Locatello F, Welling M. Rotating features for object discovery. arXiv. doi:10.48550/arXiv.2306.00600
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Published | Conference Paper | IST-REx-ID: 14208 | OA
Zhu Z, Liu F, Chrysos GG, Locatello F, Cevher V. Benign overfitting in deep neural networks under lazy training. In: Proceedings of the 40th International Conference on Machine Learning. Vol 202. ML Research Press; 2023:43105-43128.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Submitted | Preprint | IST-REx-ID: 14209 | OA
Burg MF, Wenzel F, Zietlow D, et al. A data augmentation perspective on diffusion models and retrieval. arXiv. doi:10.48550/arXiv.2304.10253
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Submitted | Preprint | IST-REx-ID: 14210 | OA
Fumero M, Wenzel F, Zancato L, et al. Leveraging sparse and shared feature activations for disentangled representation learning. arXiv. doi:10.48550/arXiv.2304.07939
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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