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9113 Publications
2023 | Conference Paper | IST-REx-ID: 14921 | 
Súkeník P, Mondelli M, Lampert C. Deep neural collapse is provably optimal for the deep unconstrained features model. In: 37th Annual Conference on Neural Information Processing Systems.
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| arXiv
2023 | Conference Paper | IST-REx-ID: 14924 |
Wu D, Kungurtsev V, Mondelli M. Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence. In: Transactions on Machine Learning Research. ML Research Press; 2023.
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| arXiv
2023 | Research Data Reference | IST-REx-ID: 14919 |
Shaw T, Buri P, McCarthy M, Miles E, Pellicciotti F. Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer. 2023. doi:10.5281/ZENODO.8277285
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2023 | Thesis | IST-REx-ID: 13107 |
Knaus L. The metabolism of the developing brain : How large neutral amino acids modulate perinatal neuronal excitability and survival. 2023. doi:10.15479/at:ista:13107
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2023 | Journal Article | IST-REx-ID: 12802 |
Knaus L, Basilico B, Malzl D, et al. Large neutral amino acid levels tune perinatal neuronal excitability and survival. Cell. 2023;186(9):1950-1967.e25. doi:10.1016/j.cell.2023.02.037
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| WoS
2023 | Preprint | IST-REx-ID: 13312 |
Valentini M, Sagi O, Baghumyan L, et al. Radio frequency driven superconducting diode and parity conserving Cooper pair transport in a two-dimensional germanium hole gas. arXiv. doi:10.48550/arXiv.2306.07109
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2023 | Journal Article | IST-REx-ID: 14949 |
Burg M, Wenzel F, Zietlow D, et al. Image retrieval outperforms diffusion models on data augmentation. Journal of Machine Learning Research. 2023.
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2023 | Preprint | IST-REx-ID: 14946 |
Yao D, Xu D, Lachapelle S, et al. Multi-view causal representation learning with partial observability. arXiv. doi:10.48550/arXiv.2311.04056
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2023 | Preprint | IST-REx-ID: 14952 |
Maiorca V, Moschella L, Norelli A, Fumero M, Locatello F, Rodolà E. Latent space translation via semantic alignment. arXiv. doi:10.48550/arXiv.2311.00664
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2023 | Preprint | IST-REx-ID: 14948 |
Kori A, Locatello F, Ribeiro FDS, Toni F, Glocker B. Grounded object centric learning. arXiv. doi:10.48550/arXiv.2307.09437
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