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5757 Publications
2021 | Conference Paper | IST-REx-ID: 14181 | 
G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, and G. Rätsch, “Boosting variational inference with locally adaptive step-sizes,” in Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, Montreal, Canada, 2021, pp. 2337–2343.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 14179 |
J. von Kügelgen et al., “Self-supervised learning with data augmentations provably isolates content from style,” in Advances in Neural Information Processing Systems, Virtual, 2021, vol. 34, pp. 16451–16467.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 14180 |
N. Rahaman et al., “Dynamic inference with neural interpreters,” in Advances in Neural Information Processing Systems, Virtual, 2021, vol. 34, pp. 10985–10998.
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| arXiv
2021 | Journal Article | IST-REx-ID: 14117 |
B. Scholkopf et al., “Toward causal representation learning,” Proceedings of the IEEE, vol. 109, no. 5. Institute of Electrical and Electronics Engineers, pp. 612–634, 2021.
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| arXiv
2021 | Conference Paper | IST-REx-ID: 14178 |
A. Dittadi et al., “On the transfer of disentangled representations in realistic settings,” in The Ninth International Conference on Learning Representations, Virtual, 2021.
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| arXiv
2021 | Preprint | IST-REx-ID: 14221 |
F. Locatello, “Enforcing and discovering structure in machine learning,” arXiv. .
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| arXiv
2021 | Preprint | IST-REx-ID: 14278 |
I. Koval, “Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse,” arXiv. .
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| arXiv
2021 | Thesis | IST-REx-ID: 10199 |
V. Toman, “Improved verification techniques for concurrent systems,” Institute of Science and Technology Austria, 2021.
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2021 | Journal Article | IST-REx-ID: 8429 |
M. Patxot et al., “Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits,” Nature Communications, vol. 12, no. 1. Springer Nature, 2021.
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| WoS
2021 | Conference Paper | IST-REx-ID: 10854 |
K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” in Abstract Proceedings of the 2021 ACM SIGMETRICS / International Conference on Measurement and Modeling of Computer Systems, Virtual, Online, 2021, pp. 71–72.
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