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4839 Publications

2021 | Published | Journal Article | IST-REx-ID: 14889 | OA
N. K. Leopold, D. J. Mitrouskas, S. A. E. Rademacher, B. Schlein, and R. Seiringer, “Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron,” Pure and Applied Analysis, vol. 3, no. 4. Mathematical Sciences Publishers, pp. 653–676, 2021.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 14890 | OA
L. Bossmann, S. P. Petrat, P. Pickl, and A. Soffer, “Beyond Bogoliubov dynamics,” Pure and Applied Analysis, vol. 3, no. 4. Mathematical Sciences Publishers, pp. 677–726, 2021.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Book Chapter | IST-REx-ID: 14984
S. Stankowski, D. Shipilina, and A. M. Westram, “Hybrid Zones,” in Encyclopedia of Life Sciences, vol. 2, Wiley, 2021.
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2021 | Published | Book Chapter | IST-REx-ID: 14987
C. Lampert, “Zero-Shot Learning,” in Computer Vision, 2nd ed., K. Ikeuchi, Ed. Cham: Springer, 2021, pp. 1395–1397.
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2021 | Research Data Reference | IST-REx-ID: 14988 | OA
A. J. Johnson, “Raw data from Johnson et al, PNAS, 2021.” Zenodo, 2021.
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2021 | Published | Journal Article | IST-REx-ID: 15013 | OA
J. Alt, L. Erdös, and T. H. Krüger, “Spectral radius of random matrices with independent entries,” Probability and Mathematical Physics, vol. 2, no. 2. Mathematical Sciences Publishers, pp. 221–280, 2021.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 14117 | OA
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.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14176 | OA
H. Yèche, G. Dresdner, F. Locatello, M. Hüser, and G. Rätsch, “Neighborhood contrastive learning applied to online patient monitoring,” in Proceedings of 38th International Conference on Machine Learning, Virtual, 2021, vol. 139, pp. 11964–11974.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14177 | OA
F. Träuble et al., “On disentangled representations learned from correlated data,” in Proceedings of the 38th International Conference on Machine Learning, Virtual, 2021, vol. 139, pp. 10401–10412.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14178 | OA
A. Dittadi et al., “On the transfer of disentangled representations in realistic settings,” in The Ninth International Conference on Learning Representations, Virtual, 2021.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14179 | OA
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.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14180 | OA
N. Rahaman et al., “Dynamic inference with neural interpreters,” in Advances in Neural Information Processing Systems, Virtual, 2021, vol. 34, pp. 10985–10998.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14181 | OA
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.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14182 | OA
F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf, and P. Gehler, “Backward-compatible prediction updates: A probabilistic approach,” in 35th Conference on Neural Information Processing Systems, Virtual, 2021, vol. 34, pp. 116–128.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Submitted | Preprint | IST-REx-ID: 14221 | OA
F. Locatello, “Enforcing and discovering structure in machine learning,” arXiv. .
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14332
F. Träuble et al., “Representation learning for out-of-distribution generalization in reinforcement learning,” in ICML 2021 Workshop on Unsupervised Reinforcement Learning, Virtual, 2021.
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2021 | Published | Journal Article | IST-REx-ID: 10000 | OA
H. M. Schmitt et al., “Increased susceptibility and intrinsic apoptotic signaling in neurons by induced HDAC3 expression,” Investigative Ophthalmology and Visual Science, vol. 62, no. 10. Association for Research in Vision and Ophthalmology, 2021.
[Published Version] View | Files available | DOI | WoS | PubMed | Europe PMC
 
2021 | Published | Conference Paper | IST-REx-ID: 10002 | OA
K. Chatterjee, W. Dvorak, M. H. Henzinger, and A. Svozil, “Symbolic time and space tradeoffs for probabilistic verification,” in Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, Rome, Italy, 2021, pp. 1–13.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10004 | OA
K. Chatterjee and L. Doyen, “Stochastic processes with expected stopping time,” in Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, Rome, Italy, 2021, pp. 1–13.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 10005 | OA
M. Bulíček, E. Maringová, and J. Málek, “On nonlinear problems of parabolic type with implicit constitutive equations involving flux,” Mathematical Models and Methods in Applied Sciences, vol. 31, no. 09. World Scientific, 2021.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

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