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Bombari, S., Kiyani, S., &; Mondelli, M. (2023). Beyond the universal law of robustness: Sharper laws for random features and neural tangent kernels. In Proceedings of the 40th International Conference on Machine Learning (Vol. 202, pp. 2738–2776). Honolulu, HI, United States: ML Research Press.
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Yao, D., Xu, D., Lachapelle, S., Magliacane, S., Taslakian, P., Martius, G.,https://doi.org/10.48550/arXiv.2311.04056__Locatello, F. (n.d.). Multi-view causal representation learning with partial observability. arXiv.https://doi.org/10.48550/arXiv.2311.04056 
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Maiorca, V., Moschella, L., Norelli, A., Fumero, M., Locatello, F., &; Rodolà, E. (n.d.). Latent space translation via semantic alignment. arXiv.https://doi.org/10.48550/arXiv.2311.00664 
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Kori, A., Locatello, F., Ribeiro, F. D. S., Toni, F., &; Glocker, B. (n.d.). Grounded object centric learning. arXiv.https://doi.org/10.48550/arXiv.2307.09437 
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Zhu, Z., Locatello, F., &; Cevher, V. (n.d.). Sample complexity bounds for score-matching: Causal discovery and generative modeling. arXiv.https://doi.org/10.48550/arXiv.2310.18123 
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Montagna, F., Mastakouri, A. A., Eulig, E., Noceti, N., Rosasco, L., Janzing, D.,https://doi.org/10.48550/arXiv.2310.13387__Locatello, F. (n.d.). Assumption violations in causal discovery and the robustness of score matching. arXiv.https://doi.org/10.48550/arXiv.2310.13387 
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Fumero, M., Wenzel, F., Zancato, L., Achille, A., Rodolà, E., Soatto, S.,https://doi.org/10.48550/arXiv.2304.07939__Locatello, F. (n.d.). Leveraging sparse and shared feature activations for disentangled representation learning. arXiv.https://doi.org/10.48550/arXiv.2304.07939 
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Löwe, S., Lippe, P., Locatello, F., &; Welling, M. (n.d.). Rotating features for object discovery. arXiv.https://doi.org/10.48550/arXiv.2306.00600 
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