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4206 Publications
2023 | Preprint | IST-REx-ID: 14946 | 
D. Yao et al., “Multi-view causal representation learning with partial observability,” arXiv. .
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2023 | Preprint | IST-REx-ID: 14952 |
V. Maiorca, L. Moschella, A. Norelli, M. Fumero, F. Locatello, and E. Rodolà, “Latent space translation via semantic alignment,” arXiv. .
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2023 | Preprint | IST-REx-ID: 14948 |
A. Kori, F. Locatello, F. D. S. Ribeiro, F. Toni, and B. Glocker, “Grounded object centric learning,” arXiv. .
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2023 | Preprint | IST-REx-ID: 14953 |
Z. Zhu, F. Locatello, and V. Cevher, “Sample complexity bounds for score-matching: Causal discovery and generative modeling,” arXiv. .
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2023 | Preprint | IST-REx-ID: 14954 |
F. Montagna et al., “Assumption violations in causal discovery and the robustness of score matching,” arXiv. .
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2023 | Preprint | IST-REx-ID: 14210 |
M. Fumero et al., “Leveraging sparse and shared feature activations for disentangled representation learning,” arXiv. .
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2023 | Preprint | IST-REx-ID: 14207 |
S. Löwe, P. Lippe, F. Locatello, and M. Welling, “Rotating features for object discovery,” arXiv. .
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2023 | Preprint | IST-REx-ID: 14961 |
F. Montagna, N. Noceti, L. Rosasco, and F. Locatello, “Shortcuts for causal discovery of nonlinear models by score matching,” arXiv. .
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2023 | Conference Paper | IST-REx-ID: 14958 |
D. Xu et al., “A sparsity principle for partially observable causal representation learning,” in Causal Representation Learning Workshop at NeurIPS 2023, New Orleans, LA, United States, 2023.
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2023 | Conference Paper | IST-REx-ID: 14923 |
T. Fu, Y. Liu, J. Barbier, M. Mondelli, S. Liang, and T. Hou, “Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise,” in Proceedings of 2023 IEEE International Symposium on Information Theory, Taipei, Taiwan.
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