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83 Publications


2024 | Published | Conference Paper | IST-REx-ID: 18847 | OA
Cadei, Riccardo, Lukas Lindorfer, Sylvia Cremer, Cordelia Schmid, and Francesco Locatello. “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, Riccardo, Francesco Locatello, Sylvia Cremer, Lukas Lindorfer, and Cordelia Schmid. “ISTAnt.” Institute of Science and Technology Austria, 2024. 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 | OA
Demirel, Berker, and Huseyin Ozkan. “Decompl: Decompositional Learning with Attention Pooling for Group Activity Recognition from a Single Volleyball Image.” In 2024 IEEE International Conference on Image Processing, 977–83. IEEE, 2024. 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 | OA
Fan, Ke, Zechen Bai, Tianjun Xiao, Tong He, Max Horn, Yanwei Fu, Francesco Locatello, and Zheng Zhang. “Adaptive Slot Attention: Object Discovery with Dynamic Slot Number.” In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE, 2024. 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 | OA
Arefin, Rifat, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, and Kenji Kawaguchi. “Unsupervised Concept Discovery Mitigates Spurious Correlations.” In Proceedings of the 41st International Conference on Machine Learning, 235:1672–88. ML Research Press, 2024.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2024 | Published | Conference Paper | IST-REx-ID: 18996 | OA
Chen, Tianyu, Kevin Bello, Francesco Locatello, Bryon Aragam, and Pradeep Kumar Ravikumar. “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, Dingling, Dario Rancati, Riccardo Cadei, Marco Fumero, and Francesco Locatello. “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, Dingling, Caroline J Muller, and Francesco Locatello. “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, Avinash, Francesco Locatello, Ainkaran Santhirasekaram, Francesca Toni, Ben Glocker, and Fabio De Sousa Ribeiro. “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, Dingling, Danru Xu, Sébastien Lachapelle, Sara Magliacane, Perouz Taslakian, Georg Martius, Julius von Kügelgen, and Francesco Locatello. “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, Dong, Zhengyang Hu, Francesco Locatello, Yanchao Yang, and Stefano Soatto. “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, Adeel A, Francesco Locatello, and Efstratios Gavves. “Mechanistic Neural Networks for Scientific Machine Learning.” In Proceedings of the 41st International Conference on Machine Learning, 235:40484–501. ML Research Press, 2024.
[Published Version] View | Files available | Download Published Version (ext.) | arXiv
 

2023 | Patent | IST-REx-ID: 14965 | OA
Ficek, Joanna, Kjong-Van Lehmann, Francesco Locatello, Gunnar Raetsch, and Stefan Stark. “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, Antonio, Marco Fumero, Valentino Maiorca, Luca Moschella, Emanuele Rodolà, and Francesco Locatello. “ASIF: Coupled Data Turns Unimodal Models to Multimodal without Training.” In 37th Conference on Neural Information Processing Systems, 36:15303–19. Curran Associates, 2023.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 

2023 | Published | Conference Paper | IST-REx-ID: 14958 | OA
Xu, Danru, Dingling Yao, Sebastien Lachapelle, Perouz Taslakian, Julius von Kügelgen, Francesco Locatello, and Sara Magliacane. “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, Samarth, Peter Gehler, Francesco Locatello, and Bernt Schiele. “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. https://doi.org/10.1109/wacv56688.2023.00278.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Submitted | Preprint | IST-REx-ID: 14207 | OA
Löwe, Sindy, Phillip Lippe, Francesco Locatello, and Max Welling. “Rotating Features for Object Discovery.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2306.00600.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Published | Conference Paper | IST-REx-ID: 14208 | OA
Zhu, Zhenyu, Fanghui Liu, Grigorios G Chrysos, Francesco Locatello, and Volkan Cevher. “Benign Overfitting in Deep Neural Networks under Lazy Training.” In Proceedings of the 40th International Conference on Machine Learning, 202:43105–28. ML Research Press, 2023.
[Preprint] View | Download Preprint (ext.) | arXiv
 

2023 | Submitted | Preprint | IST-REx-ID: 14209 | OA
Burg, Max F., Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, and Chris Russell. “A Data Augmentation Perspective on Diffusion Models and Retrieval.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2304.10253.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

2023 | Submitted | Preprint | IST-REx-ID: 14210 | OA
Fumero, Marco, Florian Wenzel, Luca Zancato, Alessandro Achille, Emanuele Rodolà, Stefano Soatto, Bernhard Schölkopf, and Francesco Locatello. “Leveraging Sparse and Shared Feature Activations for Disentangled Representation Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2304.07939.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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