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4858 Publications
2023 |
Research Data Reference |
IST-REx-ID: 14919 |
T. Shaw, P. Buri, M. McCarthy, E. Miles, and F. Pellicciotti, “Air temperature and near-surface meteorology datasets on three Swiss glaciers - Extreme 2022 Summer.” Zenodo, 2023.
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2023 |
Published |
Journal Article |
IST-REx-ID: 14920 |
T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, and S. Soudjani, “Fast symbolic algorithms for mega-regular games under strong transition fairness,” TheoretiCS, vol. 2. EPI Sciences, 2023.
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| arXiv
2023 |
In Press |
Conference Paper |
IST-REx-ID: 14921 |
P. Súkeník, M. Mondelli, and C. Lampert, “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.
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| arXiv
2023 |
In Press |
Conference Paper |
IST-REx-ID: 14922 |
A. R. Esposito and M. Mondelli, “Concentration without independence via information measures,” in Proceedings of 2023 IEEE International Symposium on Information Theory, Taipei, Taiwan.
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| arXiv
2023 |
In Press |
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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| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14924 |
D. Wu, V. Kungurtsev, and M. Mondelli, “Mean-field analysis for heavy ball methods: Dropout-stability, connectivity, and global convergence,” in Transactions on Machine Learning Research, 2023.
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| arXiv
2023 |
Submitted |
Preprint |
IST-REx-ID: 14946 |
D. Yao et al., “Multi-view causal representation learning with partial observability,” arXiv. .
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| arXiv
2023 |
Submitted |
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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| arXiv
2023 |
Published |
Journal Article |
IST-REx-ID: 14949 |
M. Burg et al., “Image retrieval outperforms diffusion models on data augmentation,” Journal of Machine Learning Research. ML Research Press, 2023.
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2023 |
Submitted |
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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| arXiv
2023 |
Submitted |
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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| arXiv
2023 |
Submitted |
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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| arXiv
2023 |
Published |
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 |
Submitted |
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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| arXiv
2023 |
Published |
Journal Article |
IST-REx-ID: 14985 |
Z. Liu et al., “Lattice expansion enables interstitial doping to achieve a high average ZT in n‐type PbS,” Interdisciplinary Materials, vol. 2, no. 1. Wiley, pp. 161–170, 2023.
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2023 |
Published |
Conference Paper |
IST-REx-ID: 14989 |
H. Malvai et al., “Parakeet: Practical key transparency for end-to-end eEncrypted messaging,” in Proceedings of the 2023 Network and Distributed System Security Symposium, San Diego, CA, United States, 2023.
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2023 |
Research Data Reference |
IST-REx-ID: 14990 |
T. Meggendorfer, “Artefact for: Correct Approximation of Stationary Distributions.” Zenodo, 2023.
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2023 |
Research Data Reference |
IST-REx-ID: 14991 |
Y.-L. Hwong, M. Colin, P. Aglas, C. J. Muller, and S. C. Sherwood, “Data-assessing memory in convection schemes using idealized tests.” Zenodo, 2023.
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2023 |
Published |
Book Chapter |
IST-REx-ID: 14992 |
M. Lewin, E. H. Lieb, and R. Seiringer, “Universal Functionals in Density Functional Theory,” in Density Functional Theory, 1st ed., E. Cances and G. Friesecke, Eds. Springer, 2023, pp. 115–182.
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| arXiv
2023 |
Published |
Conference Paper |
IST-REx-ID: 14993 |
C. Currin et al., “A framework for grassroots research collaboration in machine learning and global health,” in 1st Workshop on Machine Learning & Global Health, Kigali, Rwanda, 2023.
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