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4839 Publications

2021 | Published | Journal Article | IST-REx-ID: 14889 | OA
Landau–Pekar equations and quantum fluctuations for the dynamics of a strongly coupled polaron
N.K. Leopold, D.J. Mitrouskas, S.A.E. Rademacher, B. Schlein, R. Seiringer, Pure and Applied Analysis 3 (2021) 653–676.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 14890 | OA
Beyond Bogoliubov dynamics
L. Bossmann, S.P. Petrat, P. Pickl, A. Soffer, Pure and Applied Analysis 3 (2021) 677–726.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Book Chapter | IST-REx-ID: 14984
Hybrid Zones
S. Stankowski, D. Shipilina, A.M. Westram, in:, Encyclopedia of Life Sciences, Wiley, 2021.
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2021 | Published | Book Chapter | IST-REx-ID: 14987
Zero-Shot Learning
C. Lampert, in:, K. Ikeuchi (Ed.), Computer Vision, 2nd ed., Springer, Cham, 2021, pp. 1395–1397.
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2021 | Research Data Reference | IST-REx-ID: 14988 | OA
Raw data from Johnson et al, PNAS, 2021
A.J. Johnson, (2021).
[Published Version] View | Files available | DOI | Download Published Version (ext.)
 
2021 | Published | Journal Article | IST-REx-ID: 15013 | OA
Spectral radius of random matrices with independent entries
J. Alt, L. Erdös, T.H. Krüger, Probability and Mathematical Physics 2 (2021) 221–280.
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 14117 | OA
Toward causal representation learning
B. Scholkopf, F. Locatello, S. Bauer, N.R. Ke, N. Kalchbrenner, A. Goyal, Y. Bengio, Proceedings of the IEEE 109 (2021) 612–634.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14176 | OA
Neighborhood contrastive learning applied to online patient monitoring
H. Yèche, G. Dresdner, F. Locatello, M. Hüser, G. Rätsch, in:, Proceedings of 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 11964–11974.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14177 | OA
On disentangled representations learned from correlated data
F. Träuble, E. Creager, N. Kilbertus, F. Locatello, A. Dittadi, A. Goyal, B. Schölkopf, S. Bauer, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 10401–10412.
[Published Version] View | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14178 | OA
On the transfer of disentangled representations in realistic settings
A. Dittadi, F. Träuble, F. Locatello, M. Wüthrich, V. Agrawal, O. Winther, S. Bauer, B. Schölkopf, in:, The Ninth International Conference on Learning Representations, 2021.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14179 | OA
Self-supervised learning with data augmentations provably isolates content from style
J. von Kügelgen, Y. Sharma, L. Gresele, W. Brendel, B. Schölkopf, M. Besserve, F. Locatello, in:, Advances in Neural Information Processing Systems, 2021, pp. 16451–16467.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14180 | OA
Dynamic inference with neural interpreters
N. Rahaman, M.W. Gondal, S. Joshi, P. Gehler, Y. Bengio, F. Locatello, B. Schölkopf, in:, Advances in Neural Information Processing Systems, 2021, pp. 10985–10998.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14181 | OA
Boosting variational inference with locally adaptive step-sizes
G. Dresdner, S. Shekhar, F. Pedregosa, F. Locatello, G. Rätsch, in:, Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, International Joint Conferences on Artificial Intelligence, 2021, pp. 2337–2343.
[Published Version] View | DOI | Download Published Version (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14182 | OA
Backward-compatible prediction updates: A probabilistic approach
F. Träuble, J. von Kügelgen, M. Kleindessner, F. Locatello, B. Schölkopf, P. Gehler, in:, 35th Conference on Neural Information Processing Systems, 2021, pp. 116–128.
[Preprint] View | Download Preprint (ext.) | arXiv
 
2021 | Submitted | Preprint | IST-REx-ID: 14221 | OA
Enforcing and discovering structure in machine learning
F. Locatello, ArXiv (n.d.).
[Preprint] View | DOI | Download Preprint (ext.) | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 14332
Representation learning for out-of-distribution generalization in reinforcement learning
F. Träuble, A. Dittadi, M. Wuthrich, F. Widmaier, P.V. Gehler, O. Winther, F. Locatello, O. Bachem, B. Schölkopf, S. Bauer, in:, ICML 2021 Workshop on Unsupervised Reinforcement Learning, 2021.
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2021 | Published | Journal Article | IST-REx-ID: 10000 | OA
Increased susceptibility and intrinsic apoptotic signaling in neurons by induced HDAC3 expression
H.M. Schmitt, R.L. Fehrman, M.E. Maes, H. Yang, L.W. Guo, C.L. Schlamp, H.R. Pelzel, R.W. Nickells, Investigative Ophthalmology and Visual Science 62 (2021).
[Published Version] View | Files available | DOI | WoS | PubMed | Europe PMC
 
2021 | Published | Conference Paper | IST-REx-ID: 10002 | OA
Symbolic time and space tradeoffs for probabilistic verification
K. Chatterjee, W. Dvorak, M.H. Henzinger, A. Svozil, in:, Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, Institute of Electrical and Electronics Engineers, 2021, pp. 1–13.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2021 | Published | Conference Paper | IST-REx-ID: 10004 | OA
Stochastic processes with expected stopping time
K. Chatterjee, L. Doyen, in:, Proceedings of the 36th Annual ACM/IEEE Symposium on Logic in Computer Science, Institute of Electrical and Electronics Engineers, 2021, pp. 1–13.
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 
2021 | Published | Journal Article | IST-REx-ID: 10005 | OA
On nonlinear problems of parabolic type with implicit constitutive equations involving flux
M. Bulíček, E. Maringová, J. Málek, Mathematical Models and Methods in Applied Sciences 31 (2021).
[Preprint] View | DOI | Download Preprint (ext.) | WoS | arXiv
 

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