M. Phuong, “Underspecification in deep learning,” Institute of Science and Technology Austria, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9418
DOI: 10.15479/AT:ISTA:9418

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.
LibreCat: https://research-explorer.ista.ac.at/record/14177
arXiv: 2006.07886

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.
LibreCat: https://research-explorer.ista.ac.at/record/14176
arXiv: 2106.05142

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.
LibreCat: https://research-explorer.ista.ac.at/record/14182
arXiv: 2107.01057

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.
LibreCat: https://research-explorer.ista.ac.at/record/14181
DOI: 10.24963/ijcai.2021/322
arXiv: 2105.09240

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.
LibreCat: https://research-explorer.ista.ac.at/record/14179
arXiv: 2106.04619

N. Rahaman et al., “Dynamic inference with neural interpreters,” in Advances in Neural Information Processing Systems, Virtual, 2021, vol. 34, pp. 10985–10998.
LibreCat: https://research-explorer.ista.ac.at/record/14180
arXiv: 2110.06399

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.
LibreCat: https://research-explorer.ista.ac.at/record/14117
DOI: 10.1109/jproc.2021.3058954
arXiv: 2102.11107

A. Dittadi et al., “On the transfer of disentangled representations in realistic settings,” in The Ninth International Conference on Learning Representations, Virtual, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/14178
arXiv: 2010.14407

F. Locatello, “Enforcing and discovering structure in machine learning,” arXiv. .
LibreCat: https://research-explorer.ista.ac.at/record/14221
DOI: 10.48550/arXiv.2111.13693
arXiv: 2111.13693

I. Koval, “Local strong Birkhoff conjecture and local spectral rigidity of almost every ellipse,” arXiv. .
LibreCat: https://research-explorer.ista.ac.at/record/14278
DOI: 10.48550/ARXIV.2111.12171
arXiv: 2111.12171

V. Toman, “Improved verification techniques for concurrent systems,” Institute of Science and Technology Austria, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/10199
DOI: 10.15479/at:ista:10199

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.
LibreCat: https://research-explorer.ista.ac.at/record/8429
DOI: 10.1038/s41467-021-27258-9
WoS: 000724450600023

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.
LibreCat: https://research-explorer.ista.ac.at/record/10854
DOI: 10.1145/3410220.3453923
arXiv: 2005.07637

K.-T. Foerster, J. Korhonen, A. Paz, J. Rybicki, and S. Schmid, “Input-dynamic distributed algorithms for communication networks,” Proceedings of the ACM on Measurement and Analysis of Computing Systems, vol. 5, no. 1. Association for Computing Machinery, pp. 1–33, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/10855
DOI: 10.1145/3447384
arXiv: 2005.07637

K. Chatterjee, W. Dvoák, M. H. Henzinger, and A. Svozil, “Algorithms and conditional lower bounds for planning problems,” Artificial Intelligence, vol. 297, no. 8. Elsevier, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9293
DOI: 10.1016/j.artint.2021.103499
WoS: 000657537500003
arXiv: 1804.07031

M. R. Robinson, “Probabilistic inference of the genetic architecture of functional enrichment of complex traits.” Dryad, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/13063
DOI: 10.5061/dryad.sqv9s4n51

Y. Zhang et al., “Influence of copper telluride nanodomains on the transport properties of n-type bismuth telluride,” Chemical Engineering Journal, vol. 418, no. 8. Elsevier, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9304
DOI: 10.1016/j.cej.2021.129374
WoS: 000655672000005

K. T. Baldwin et al., “HepaCAM controls astrocyte self-organization and coupling,” Neuron, vol. 109, no. 15. Elsevier, p. 2427–2442.e10, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9793
DOI: 10.1016/j.neuron.2021.05.025
WoS: 000692851900010
PMID: 34171291

Y. Zhang et al., “Doping-mediated stabilization of copper vacancies to promote thermoelectric properties of Cu2-xS,” Nano Energy, vol. 85, no. 7. Elsevier, 2021.
LibreCat: https://research-explorer.ista.ac.at/record/9305
DOI: 10.1016/j.nanoen.2021.105991
WoS: 000663442200004