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100 Publications


2026 | Accepted | Conference Paper | IST-REx-ID: 21113 | OA
Montagna, F. (n.d.). On the identifiability of causal graphs with multiple environments. In The 14th International Conference on Learning Representations. Rio de Janeiro, Brazil: OpenReview.
[Published Version] View | Download Published Version (ext.) | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 20032 | OA
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
 

2025 | Published | Conference Paper | IST-REx-ID: 20036 | OA
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: 20303 | OA
Huang, S., Pfister, N., & Bowden, J. (2025). Sparse causal effect estimation using two-sample summary statistics in the presence of unmeasured confounding. In The 28th International Conference on Artificial Intelligence and Statistics (Vol. 258, pp. 3394–3402). Mai Khao, Thailand: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 20592 | OA
Yao, D., Tronarp, F., & Bosch, N. (2025). Propagating model uncertainty through filtering-based probabilistic numerical ODE solvers. In Proceedings of the 1st International Conference on Probabilistic Numerics (Vol. 271). Sophia Antipolis, France: ML Research Press.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 20817 | OA
Pervez, A. A., Gavves, E., & Locatello, F. (2025). Mechanistic PDE networks for discovery of governing equations. In 42nd International Conference on Machine Learning (Vol. 267, pp. 48962–48973). Vancouver, Canada: ML Research Press.
[Published Version] View | Files available | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 19010 | OA
Yao, D., Rancati, D., Cadei, R., Fumero, M., & Locatello, F. (2025). Unifying causal representation learning with the invariance principle. In 13th International Conference on Learning Representations. Singapore: ICLR.
[Published Version] View | Files available | arXiv
 

2025 | Submitted | Preprint | IST-REx-ID: 19674 | OA
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 | Journal Article | IST-REx-ID: 20934 | OA | PlanS
Montagna, F., Cairney-Leeming, M. T., Sridhar, D., & Locatello, F. (2025). Demystifying amortized causal discovery with transformers. Transactions on Machine Learning Research. ML Research Press.
[Published Version] View | Files available | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 21049 | OA
Gairola, S., Böhle, M., Locatello, F., & Schiele, B. (2025). How to probe: Simple yet effective techniques for improving post-hoc explanations. In 13th International Conference on Learning Representations. Singapore: ICLR.
[Published Version] View | Files available | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 21066 | OA
Montagna, F., Faller, P., Blöbaum, P., Kirschbaum, E., & Locatello, F. (2025). Score matching through the roof: Linear, nonlinear, and latent variables causal discovery. In Proceedings of the Fourth Conference on Causal Learning and Reasoning (Vol. 275, pp. 552–605). Lausanne, Switzerland: ML Research Press.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2025 | Epub ahead of print | Conference Paper | IST-REx-ID: 21068 | OA
Yao, D., Huang, S., Cadei, R., Zhang, K., & Locatello, F. (2025). The third pillar of causal analysis? A measurement perspective on causal representations. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2025 | Epub ahead of print | Conference Paper | IST-REx-ID: 21070 | OA
Demirel, B., Fumero, M., & Locatello, F. (2025). Out-of-Distribution detection with relative angles. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2025 | Epub ahead of print | Conference Paper | IST-REx-ID: 21072 | OA
Basile, L., Maiorca, V., Doimo, D., Locatello, F., & Cazzaniga, A. (2025). Head pursuit: Probing attention specialization in multimodal transformers. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2025 | Epub ahead of print | Conference Paper | IST-REx-ID: 21074 | OA
Yu, H., Inal, B., Arvanitidis, G., Hauberg, S., Locatello, F., & Fumero, M. (2025). Connecting neural models latent geometries with relative geodesic representations. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.
[Published Version] View | Files available | arXiv
 

2025 | Epub ahead of print | Conference Paper | IST-REx-ID: 21076 | OA
Cadei, R., Demirel, I., De Bartolomeis, P., Lindorfer, L., Cremer, S., Schmid, C., & Locatello, F. (2025). Prediction-powered causal inferences. In 39th Annual Conference on Neural Information Processing Systems (Vol. 38). San Diego, CA, United States: Neural Information Processing Systems Foundation.
[Published Version] View | Files available
 

2024 | Published | Conference Paper | IST-REx-ID: 14213 | OA
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 | OA
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 | Published | Conference Paper | IST-REx-ID: 18847 | OA
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
 

2024 | Research Data Reference | IST-REx-ID: 18895 | OA
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.)
 

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