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100 Publications


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

2025 | Published | Conference Paper | IST-REx-ID: 20032 | OA
J. Chen, D. Yao, A. A. Pervez, D.-A. Alistarh, and F. Locatello, “Scalable mechanistic neural networks,” in 13th International Conference on Learning Representations, Singapore, Singapore, 2025, pp. 63716–63737.
[Published Version] View | Files available | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 20036 | OA
V. Pariza, M. Salehi, G. Burghouts, F. Locatello, and Y. M. Asano, “Near, far: Patch-ordering enhances vision foundation models’ scene understanding,” in 13th International Conference on Learning Representations, Singapore, Singapore, 2025, pp. 72303–72330.
[Published Version] View | Files available | arXiv
 

2025 | Published | Conference Paper | IST-REx-ID: 20303 | OA
S. Huang, N. Pfister, and J. Bowden, “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, Mai Khao, Thailand, 2025, vol. 258, pp. 3394–3402.
[Preprint] View | Download Preprint (ext.) | arXiv
 

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

2025 | Published | Conference Paper | IST-REx-ID: 20817 | OA
A. A. Pervez, E. Gavves, and F. Locatello, “Mechanistic PDE networks for discovery of governing equations,” in 42nd International Conference on Machine Learning, Vancouver, Canada, 2025, vol. 267, pp. 48962–48973.
[Published Version] View | Files available | arXiv
 

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

2025 | Submitted | Preprint | IST-REx-ID: 19674 | OA
L. Basile, V. Maiorca, L. Bortolussi, E. Rodolà, and F. Locatello, “ResiDual transformer alignment with spectral decomposition,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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

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

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

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

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

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

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

2025 | Epub ahead of print | Conference Paper | IST-REx-ID: 21076 | OA
R. Cadei et al., “Prediction-powered causal inferences,” in 39th Annual Conference on Neural Information Processing Systems, San Diego, CA, United States, 2025, vol. 38.
[Published Version] View | Files available
 

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

2024 | Published | Conference Paper | IST-REx-ID: 18114 | OA
A. A. Pervez, F. Locatello, and E. Gavves, “Mechanistic neural networks for scientific machine learning,” in Proceedings of the 41st International Conference on Machine Learning, Vienna, Austria, 2024, vol. 235, pp. 40484–40501.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

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

2024 | Research Data Reference | IST-REx-ID: 18895 | OA
R. Cadei, F. Locatello, S. Cremer, L. Lindorfer, and C. Schmid, “ISTAnt.” Institute of Science and Technology Austria, 2024.
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 

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