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.

Sinha, Samarth, Peter Gehler, Francesco Locatello, and Bernt Schiele. “TeST: Test-Time Self-Training under Distribution Shift.”https://doi.org/10.1109/wacv56688.2023.00278__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 .

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.

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.”https://doi.org/10.48550/arXiv.2304.10253__ArXiv, n.d.https://doi.org/10.48550/arXiv.2304.10253 .

Montagna, Francesco, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, and Francesco Locatello. “Causal Discovery with Score Matching on Additive Models with Arbitrary Noise.” In 2nd Conference on Causal Learning and Reasoning, 2023.

Montagna, Francesco, Nicoletta Noceti, Lorenzo Rosasco, Kun Zhang, and Francesco Locatello. “Scalable Causal Discovery with Score Matching.” In 2nd Conference on Causal Learning and Reasoning, 2023.

Liu, Yuejiang, Alexandre Alahi, Chris Russell, Max Horn, Dominik Zietlow, Bernhard Schölkopf, and Francesco Locatello. “Causal Triplet: An Open Challenge for Intervention-Centric Causal Representation Learning.” In 2nd Conference on Causal Learning and Reasoning, 2023.

Moschella, Luca, Valentino Maiorca, Marco Fumero, Antonio Norelli, Francesco Locatello, and Emanuele Rodolà. “Relative Representations Enable Zero-Shot Latent Space Communication.” In The 11th International Conference on Learning Representations, 2023.

Tangemann, Matthias, Steffen Schneider, Julius von Kügelgen, Francesco Locatello, Peter Gehler, Thomas Brox, Matthias Kümmerer, Matthias Bethge, and Bernhard Schölkopf. “Unsupervised Object Learning via Common Fate.” In 2nd Conference on Causal Learning and Reasoning, 2023.

Seitzer, Maximilian, Max Horn, Andrii Zadaianchuk, Dominik Zietlow, Tianjun Xiao, Carl-Johann Simon-Gabriel Carl-Johann Simon-Gabriel, Tong He, et al. “Bridging the Gap to Real-World Object-Centric Learning.” In The 11th International Conference on Learning Representations, 2023.

Zadaianchuk, Andrii, Matthaeus Kleindessner, Yi Zhu, Francesco Locatello, and Thomas Brox. “Unsupervised Semantic Segmentation with Self-Supervised Object-Centric Representations.” In The 11th International Conference on Learning Representations, 2023.

Faller, Philipp M., Leena Chennuru Vankadara, Atalanti A. Mastakouri, Francesco Locatello, and Dominik Janzing. “Self-Compatibility: Evaluating Causal Discovery without Ground Truth.”https://doi.org/10.48550/arXiv.2307.09552__ArXiv, n.d.https://doi.org/10.48550/arXiv.2307.09552 .

Burg, Max, Florian Wenzel, Dominik Zietlow, Max Horn, Osama Makansi, Francesco Locatello, and Chris Russell. “Image Retrieval Outperforms Diffusion Models on Data Augmentation.” Journal of Machine Learning Research. ML Research Press, 2023.

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.”https://doi.org/10.48550/arXiv.2311.04056__ArXiv, n.d.https://doi.org/10.48550/arXiv.2311.04056 .

Maiorca, Valentino, Luca Moschella, Antonio Norelli, Marco Fumero, Francesco Locatello, and Emanuele Rodolà. “Latent Space Translation via Semantic Alignment.”https://doi.org/10.48550/arXiv.2311.00664__ArXiv, n.d.https://doi.org/10.48550/arXiv.2311.00664 .

Kori, Avinash, Francesco Locatello, Fabio De Sousa Ribeiro, Francesca Toni, and Ben Glocker. “Grounded Object Centric Learning.”https://doi.org/10.48550/arXiv.2307.09437__ArXiv, n.d.https://doi.org/10.48550/arXiv.2307.09437 .

Zhu, Zhenyu, Francesco Locatello, and Volkan Cevher. “Sample Complexity Bounds for Score-Matching: Causal Discovery and Generative Modeling.”https://doi.org/10.48550/arXiv.2310.18123__ArXiv, n.d.https://doi.org/10.48550/arXiv.2310.18123 .

Montagna, Francesco, Atalanti A. Mastakouri, Elias Eulig, Nicoletta Noceti, Lorenzo Rosasco, Dominik Janzing, Bryon Aragam, and Francesco Locatello. “Assumption Violations in Causal Discovery and the Robustness of Score Matching.”https://doi.org/10.48550/arXiv.2310.13387__ArXiv, n.d.https://doi.org/10.48550/arXiv.2310.13387 .

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.”https://doi.org/10.48550/arXiv.2304.07939__ArXiv, n.d.https://doi.org/10.48550/arXiv.2304.07939 .

Löwe, Sindy, Phillip Lippe, Francesco Locatello, and Max Welling. “Rotating Features for Object Discovery.”https://doi.org/10.48550/arXiv.2306.00600__ArXiv, n.d.https://doi.org/10.48550/arXiv.2306.00600 .