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4964 Publications

2023 | Conference Paper | IST-REx-ID: 12859 | OA
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.
[Preprint] View | Files available | Download Preprint (ext.) | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14921 | OA
Súkeník, P., Mondelli, M., & Lampert, C. (n.d.). Deep neural collapse is provably optimal for the deep unconstrained features model. In 37th Annual Conference on Neural Information Processing Systems. New Orleans, LA, United States.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2023 | Conference Paper | IST-REx-ID: 14924 | OA
Wu, D., Kungurtsev, V., & Mondelli, M. (2023). Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. In Transactions on Machine Learning Research. ML Research Press.
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2023 | Research Data Reference | IST-REx-ID: 14919 | OA
Shaw, T., Buri, P., McCarthy, M., Miles, E., & Pellicciotti, F. (2023). Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer. Zenodo. https://doi.org/10.5281/ZENODO.8277285
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2023 | Thesis | IST-REx-ID: 13107 | OA
Knaus, L. (2023). The metabolism of the developing brain : How large neutral amino acids modulate perinatal neuronal excitability and survival. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:13107
[Published Version] View | Files available | DOI
 
2023 | Journal Article | IST-REx-ID: 12802 | OA
Knaus, L., Basilico, B., Malzl, D., Gerykova Bujalkova, M., Smogavec, M., Schwarz, L. A., … Novarino, G. (2023). Large neutral amino acid levels tune perinatal neuronal excitability and survival. Cell. Elsevier. https://doi.org/10.1016/j.cell.2023.02.037
[Published Version] View | Files available | DOI | WoS
 
2023 | Preprint | IST-REx-ID: 13312 | OA
Valentini, M., Sagi, O., Baghumyan, L., Gijsel, T. de, Jung, J., Calcaterra, S., … Katsaros, G. (n.d.). Radio frequency driven superconducting diode and parity conserving  Cooper pair transport in a two-dimensional germanium hole gas. arXiv. https://doi.org/10.48550/arXiv.2306.07109
[Preprint] View | Files available | DOI | Download Preprint (ext.) | arXiv
 
2023 | Journal Article | IST-REx-ID: 14949 | OA
Burg, M., Wenzel, F., Zietlow, D., Horn, M., Makansi, O., Locatello, F., & Russell, C. (2023). Image retrieval outperforms diffusion models on data augmentation. Journal of Machine Learning Research. ML Research Press.
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2023 | Preprint | IST-REx-ID: 14946 | OA
Yao, D., Xu, D., Lachapelle, S., Magliacane, S., Taslakian, P., Martius, G., … 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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2023 | Preprint | IST-REx-ID: 14952 | OA
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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2023 | Preprint | IST-REx-ID: 14948 | OA
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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2023 | Preprint | IST-REx-ID: 14953 | OA
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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2023 | Preprint | IST-REx-ID: 14954 | OA
Montagna, F., Mastakouri, A. A., Eulig, E., Noceti, N., Rosasco, L., Janzing, D., … 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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2023 | Preprint | IST-REx-ID: 14210 | OA
Fumero, M., Wenzel, F., Zancato, L., Achille, A., Rodolà, E., Soatto, S., … 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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2023 | Preprint | IST-REx-ID: 14207 | OA
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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2023 | Preprint | IST-REx-ID: 14963 | OA
Zhao, Z., Wang, J., Horn, M., Ding, Y., He, T., Bai, Z., … Xiao, T. (n.d.). Object-centric multiple object tracking. arXiv. https://doi.org/10.48550/arXiv.2309.00233
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2023 | Preprint | IST-REx-ID: 14961 | OA
Montagna, F., Noceti, N., Rosasco, L., & Locatello, F. (n.d.). Shortcuts for causal discovery of nonlinear models by score matching. arXiv. https://doi.org/10.48550/arXiv.2310.14246
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2023 | Preprint | IST-REx-ID: 14962 | OA
Fan, K., Bai, Z., Xiao, T., Zietlow, D., Horn, M., Zhao, Z., … He, T. (n.d.). Unsupervised open-vocabulary object localization in videos. arXiv. https://doi.org/10.48550/arXiv.2309.09858
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2023 | Conference Paper | IST-REx-ID: 14958 | OA
Xu, D., Yao, D., Lachapelle, S., Taslakian, P., von Kügelgen, J., Locatello, F., & Magliacane, S. (2023). A sparsity principle for partially observable causal representation learning. In Causal Representation Learning Workshop at NeurIPS 2023. New Orleans, LA, United States: OpenReview.
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2023 | Conference Paper | IST-REx-ID: 14923 | OA
Fu, T., Liu, Y., Barbier, J., Mondelli, M., Liang, S., & Hou, T. (n.d.). Mismatched estimation of non-symmetric rank-one matrices corrupted by structured noise. In Proceedings of 2023 IEEE International Symposium on Information Theory. Taipei, Taiwan: IEEE. https://doi.org/10.1109/isit54713.2023.10206671
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 

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