Please note that LibreCat no longer supports Internet Explorer versions 8 or 9 (or earlier).
We recommend upgrading to the latest Internet Explorer, Google Chrome, or Firefox.
88 Publications
- 1 (current)
- 2
- 3
- 4
- 5
2025 | Submitted | Preprint | IST-REx-ID: 19674 | 
Basile, L., Maiorca, V., Bortolussi, L., Rodolà, E., & Locatello, F. (n.d.). ResiDual transformer alignment with spectral decomposition. arXiv. https://doi.org/10.48550/arXiv.2411.00246
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2025 | Published | Conference Paper | IST-REx-ID: 20036 |
Pariza, V., Salehi, M., Burghouts, G., Locatello, F., & Asano, Y. M. (2025). Near, far: Patch-ordering enhances vision foundation models’ scene understanding. In 13th International Conference on Learning Representations (pp. 72303–72330). Singapore, Singapore: ICLR.
[Published Version]
View
| Files available
| arXiv
2025 | Published | Conference Paper | IST-REx-ID: 20032 |
Chen, J., Yao, D., Pervez, A. A., Alistarh, D.-A., & Locatello, F. (2025). Scalable mechanistic neural networks. In 13th International Conference on Learning Representations (pp. 63716–63737). Singapore, Singapore: ICLR.
[Published Version]
View
| Files available
| arXiv
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. In 1st Conference on Parsimony and Learning. Hong Kong, China.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18114 |
Pervez, A. A., Locatello, F., & Gavves, E. (2024). Mechanistic neural networks for scientific machine learning. In Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 40484–40501). Vienna, Austria: ML Research Press.
[Published Version]
View
| Files available
| Download Published Version (ext.)
| arXiv
2024 | Research Data Reference | IST-REx-ID: 18895 |
Cadei, R., Locatello, F., Cremer, S., Lindorfer, L., & Schmid, C. (2024). ISTAnt. Institute of Science and Technology Austria. https://doi.org/10.6084/M9.FIGSHARE.26484934.V2
[Published Version]
View
| Files available
| DOI
| Download Published Version (ext.)
2024 | Published | Conference Paper | IST-REx-ID: 18956 |
Demirel, B., & Ozkan, H. (2024). Decompl: Decompositional learning with attention pooling for group activity recognition from a single volleyball image. In 2024 IEEE International Conference on Image Processing (pp. 977–983). Abu Dhabi, United Arab Emirates: IEEE. https://doi.org/10.1109/icip51287.2024.10647499
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18964 |
Fan, K., Bai, Z., Xiao, T., He, T., Horn, M., Fu, Y., … Zhang, Z. (2024). Adaptive slot attention: Object discovery with dynamic slot number. In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Seattle, WA, United States: IEEE. https://doi.org/10.1109/cvpr52733.2024.02176
[Preprint]
View
| Files available
| DOI
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18971 |
Arefin, R., Zhang, Y., Baratin, A., Locatello, F., Rish, I., Liu, D., & Kawaguchi, K. (2024). Unsupervised concept discovery mitigates spurious correlations. In Proceedings of the 41st International Conference on Machine Learning (Vol. 235, pp. 1672–1688). Vienna, Austria: ML Research Press.
[Preprint]
View
| Files available
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 14946 |
Yao, D., Xu, D., Lachapelle, S., Magliacane, S., Taslakian, P., Martius, G., … Locatello, F. (2024). Multi-view causal representation learning with partial observability. In 12th International Conference on Learning Representations. Vienna, Austria: Curran Associates.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19010 |
Yao, D., Rancati, D., Cadei, R., Fumero, M., & Locatello, F. (2024). Unifying causal representation learning with the invariance principle. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19007 |
Kori, A., Locatello, F., Santhirasekaram, A., Toni, F., Glocker, B., & De Sousa Ribeiro, F. (2024). Identifiable object-centric representation learning via probabilistic slot attention. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19515 |
Fumero, M., Pegoraro, M., Maiorca, V., Locatello, F., & Rodolà, E. (2024). Latent functional maps: A spectral framework for representation alignment. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19517 |
Crisostomi, D., Fumero, M., Baieri, D., Bernard, F., & Rodolà, E. (2024). C2M3: Cycle-consistent multi-model merging. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18996 |
Chen, T., Bello, K., Locatello, F., Aragam, B., & Ravikumar, P. K. (2024). Identifying general mechanism shifts in linear causal representations. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 19005 |
Yao, D., Muller, C. J., & Locatello, F. (2024). Marrying causal representation learning with dynamical systems for science. In 38th Conference on Neural Information Processing Systems (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.
[Published Version]
View
| Files available
| arXiv
2024 | Published | Conference Paper | IST-REx-ID: 18847 |
Cadei, R., Lindorfer, L., Cremer, S., Schmid, C., & Locatello, F. (2024). Smoke and mirrors in causal downstream tasks. In ICML 2024 Workshop AI4Science (Vol. 38). Curran Associates.
[Published Version]
View
| Files available
| 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. In 2023 IEEE/CVF Winter Conference on Applications of Computer Vision. Waikoloa, HI, United States: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/wacv56688.2023.00278
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2023 | Submitted | Preprint | IST-REx-ID: 14207 |
Löwe, S., Lippe, P., Locatello, F., & Welling, M. (n.d.). Rotating features for object discovery. arXiv. https://doi.org/10.48550/arXiv.2306.00600
[Preprint]
View
| DOI
| Download Preprint (ext.)
| arXiv
2023 | Published | Conference Paper | IST-REx-ID: 14208 |
Zhu, Z., Liu, F., Chrysos, G. G., Locatello, F., & Cevher, V. (2023). Benign overfitting in deep neural networks under lazy training. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 43105–43128). Honolulu, Hawaii, United States: ML Research Press.
[Preprint]
View
| Download Preprint (ext.)
| arXiv
- 1 (current)
- 2
- 3
- 4
- 5